{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Polynomial Regression to simulate outbreak\n",
    "\n",
    "#### Author: Yiran Jing\n",
    "\n",
    "#### Date: Feb 2020\n",
    "\n",
    "\n",
    "## Contents:\n",
    "1. EDA and Feature Engineering\n",
    "1. Polynomial regression\n",
    "   1. Chinese total comfirmed cases\n",
    "   2. For each province\n",
    "   \n",
    "## Summary\n",
    "For Polynomial regression, \n",
    "- China total comfirmed cases, optimal degree is 2, and seems fit well.\n",
    "- Hubei, optimal degree is 2.\n",
    "- Ex-hubei, optimal degree is 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import operator\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import pandas\n",
    "import datetime\n",
    "import matplotlib.dates as mdates\n",
    "from helper_fun_model import *\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from sklearn.preprocessing import PolynomialFeatures\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-21 00:16:23Update records successfully to ../data/DXY_Chinese.csv\n",
      "Save area daily dataset (English) into ../data/DXYArea.csv\n",
      "CPU times: user 225 ms, sys: 73.7 ms, total: 298 ms\n",
      "Wall time: 18 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "## Update data from DXY\n",
    "! cd ../data_processing && python DXY_AreaData_query.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>country</th>\n",
       "      <th>countryCode</th>\n",
       "      <th>province</th>\n",
       "      <th>city</th>\n",
       "      <th>confirmed</th>\n",
       "      <th>suspected</th>\n",
       "      <th>cured</th>\n",
       "      <th>dead</th>\n",
       "      <th>Days</th>\n",
       "      <th>net_confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9229</th>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>泰国</td>\n",
       "      <td>TH</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>17</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9230</th>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>美国</td>\n",
       "      <td>US</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9231</th>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>越南</td>\n",
       "      <td>VN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date country countryCode province city  confirmed  suspected  \\\n",
       "9229 2020-02-20      泰国          TH      NaN  NaN         35          0   \n",
       "9230 2020-02-20      美国          US      NaN  NaN         15          0   \n",
       "9231 2020-02-20      越南          VN      NaN  NaN         16          0   \n",
       "\n",
       "      cured  dead  Days  net_confirmed  \n",
       "9229     17     0    74             18  \n",
       "9230      3     0    74             12  \n",
       "9231      9     0    74              7  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Load data \n",
    "df = pd.read_csv(\"../data/DXYArea.csv\")\n",
    "\"\"\"\n",
    "Data Cleaning \n",
    "\"\"\"\n",
    "df['date'] = pd.to_datetime(df['date'])\n",
    "df = df[df['date'] != df['date'].max()] # remove todays' records (since it can be incompleted)\n",
    "#df = df[df['date'] < datetime.datetime(2020, 2, 10)]\n",
    "\n",
    "df.tail(3) # check new"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### EDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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yYOP0lNKvG5S/LddHZ13Tq2nLcUgp/TEippDNNP5C/p1RP9P4GLK+Th8B/ivPv6af9YYuJbvuf5T/YDKdrFZ7JFltcn1Nt9TjGXBIpdEwiCg0v8afyAKOFXwwatJKeVOBw8k6m3+XrEbkl2SdPVvTbKCglNLbEbE/8EOyOQb6kQ39eRBwIkUIOPL93h0RW5E1CTqA7MZmLbL24g+T3RhVN1jlq2S/rH6GLCB5imwIzCkUIeDIHUs20tWE/O8/k90sXEn2a3+TUkor8vkNLiSbp2AQ2S/hx+flbXxzdhNZu/OjyW7e+5AFVC3dnFWRzeewHtk5LFSWeyNiF7LahWPImny8BbwEXEzL81jU11qcFBE3k91gHkvWaXgp2S/El5PNt1GfvzayOSfOy/c5mCyY/T7ZELWlnjm9w6SUno5sUrezyG7sv0jWpGwmWaDxQIO8j0bEJ4EfkJ2Pd4Bbya6pfxbY/Lpk/QWa6/Te2JX58/v59l8gC0qnpZRW6yDf2uujE6/pQtp0HFJKV0fEw2TfL/uS9W/qQzZ3yHTgc2nVeTra/VlvtN9l+TH6cr6d+oEEXiMb+rhHBNpSa0SDUQclSVIXlPd3eROY2rjPRG/icZC6J/twSJLU9e1HdqNdsOaqF/E4SN2QNRySJEmSisYaDkmSJElFY8AhSZIkqWgMOCRJkiQVjQGHJEmSpKIx4JAkSZJUNAYckiRJkorGgEOSJElS0RhwSJIkSSoaAw5JkiRJRWPAIUmSJKloDDgkSZIkFY0BhyRJkqSiMeCQJEmSVDQGHJIkSZKKxoBDkiRJUtEYcEiSJEkqGgMOSZIkSUVjwCFJkiSpaAw4JEmSJBWNAYckSZKkojHgkCRJklQ0BhySJEmSisaAQ5IkSVLRGHBIkiRJKhoDDkmSJElFY8AhSZIkqWgMOCRJkiQVjQGHJEmSpKIx4JAkSZJUNAYckiRJkorGgEOSJElS0RhwSJIkSSoaAw5JkiRJRWPAIUmSJKloDDgkSZIkFY0BhyRJkqSiMeCQJEmSVDQGHJIkSZKKxoBDkiRJUtEYcEiSJEkqGgMOSZIkSUVjwCFJkiSpaAw4JEmSJBWNAYckSZKkojHgkCRJklQ0BhySJEmSisaAQ5IkSVLRGHBIkiRJKhoDDkmSJElFY8AhSZIkqWgMOCRJkiQVjQGHJEmSpKIx4JAkSZJUNAYckiRJkoqmX6kLUGqDBw9OY8aMKXUx1IkWLlzIoEGDSl0M9VBeX72T513F5PXV+3THc/7UU0/9J6U0tNCyXh9wDBs2jCeffLLUxVAnqq6uZty4caUuhnoor6/eyfOuYvL66n264zmPiNqmltmkSpIkSVLRGHBIkiRJKhoDDkmSJElF0+v7cBSybNky5syZw5IlS0pdlB5jwIABjBgxgrXWWqvURZEkSVInMuAoYM6cOay77rqMGjWKiCh1cbq9lBLz5s1jzpw5jB49utTFkSRJUieySVUBS5YsYciQIQYbHSQiGDJkiDVGkiRJvZABRxMMNjqWx1OSJKnnqaqqYtSoUQA7NZXHJlWSJEmS2qyqqoopU6awaNGiZvNZw9GDnXHGGWyzzTacccYZ/OxnP+P6668v+j6rq6v59Kc/XfT9SJIkqbjqay/69OnDqFGjqKqqWrls5syZfOUrX2kx2ABrODpEVVUVFRUVzJo1i5EjRzJ16lQmTJhQ6mJRWVnJ/Pnz6du3b5N5li9fTr9+XgaSJEn6QOPai9raWiZPnsytt97Kyy+/zDPPPNPqbVnDsYbqT0ZtbS0pJWpra5kyZcoqEWB7XH/99Wy33XZ89KMf5dhjj2XmzJnss88+bLfdduy7777MmjULgIkTJ3LaaafxsY99jM0224xbb70VgEMPPZQFCxaw0047cfPNN3POOedw4YUXAjBu3DhOP/10dt55Zy699FImTpzIl770JXbffXc222wzqqurOeGEE9hqq62YOHHiyjLdd9997LHHHuy4444cddRRLFiwAIA//OEPbLnlluy4447cdttta/S+JUmSVHoVFRWr1V4sWbKE3/72t6y//vpceOGFbLLJJq3alj9tt+D000/n6aefbnL5Y489xtKlS1dJW7RoESeeeCK/+MUvCq6z/fbb8+Mf/7jJbT777LOcf/75/OUvf2HDDTdk/vz5HH/88Ssf06ZN47TTTuO3v/0tAK+//joPP/ww//rXvzj00EM58sgjufPOO1lnnXVWlv2cc85ZZR/vv/8+Tz75JJAFLW+99RaPPvood955J4ceeiiPPPIIV111FbvssgtPP/00I0aM4Pzzz+f+++9n0KBBXHDBBVx88cV84xvf4KSTTmL69OmMGTOGz3/+8y0eU0mSJHVt9T9uNxYRPPTQQwB8+MMftg9HZ2gcbLSU3hrTp0/nqKOOYsMNNwTgQx/6EI8++ihf+MIXADj22GN5+OGHV+Y//PDD6dOnD1tvvTVz585t1T4aBwaHHHIIEcG2227LsGHD2HbbbenTpw/bbLMNM2fO5LHHHuO5555jzz33ZPvtt+e6666jtraWf/3rX4wePZqxY8cSERxzzDHtft+SJEnqGkaMGFEwfeTIkSv/njBhApWVlZSXlze7LWs4WtBcTQTAqFGjqK2tXS29vLyc6urqIpVqVWuvvfbKv1NKrVpn0KBBBbfRp0+fVbbXp08fli9fTt++ffnkJz/JTTfdtMp6zdX+SJIkqftJKfHhD3+Y2bNnr5JeVlbG1KlTV0mbMGECEyZMICKeamp71nCsoalTp1JWVrZKWqGT0Rb77LMPv/71r5k3bx4A8+fP52Mf+xi/+tWvgKzfyF577dX+QrfD7rvvziOPPMKMGTMAWLhwITU1NWy55ZbMnDmTl156CWC1gESSJEndy/e//32eeOIJxo8fT3l5ORFBeXk5lZWV7RoYyRqONVR/0DtylKptttmGiooK9t57b/r27csOO+zAZZddxqRJk/jRj37E0KFDueaaazrqLbTK0KFDufbaaxk/fvzK5mLnn38+m2++OZWVlRx88MGUlZWx11578d5773Vq2SRJktQx7r77br71rW/xhS98gRtuuKFDJm+O1jbB6am22GKL9MILL6yS9vzzz7PVVluVqEQ9V1c5rtXV1YwbN67UxVAP5fXVO3neVUxeX71Pqc75Cy+8wK677spHPvIRHn744dVa8TQnIp5KKe1caJlNqiRJkqRe7p133uGwww6jf//+3H777W0KNlpikypJkiSpF6urq+PYY49lxowZPPDAAy2OOtVWBhxNSCl1SJs1ZXp70z1JkqSu6txzz+Wuu+7isssuY++99+7w7dukqoABAwYwb948b5I7SEqJefPmMWDAgFIXRZIkSQ3cfvvtnHfeeUyaNIlTTjmlKPuwhqOAESNGMGfOHN58881SF6XHGDBgQJMTyEiSJKnzPfvssxx33HHsuuuuXHHFFUVr3WPAUcBaa63F6NGjS10MSZIkqSjeeustDj/8cAYNGsRtt91W1JYoBhySJElSL7JixQrGjx9PbW0t1dXVDB8+vKj7M+CQJEmSepGKigruvfdeKisr+djHPlb0/dlpXJIkSeolbr75Zi644AK++MUvctJJJ3XKPg04JEmSpF7gH//4B5MmTWLPPffk0ksv7bT9GnBIkiRJPdx//vMfDj/8cD70oQ9x66230r9//07bd6cHHBHRNyL+HhG/y1+PjojHI2JGRNwcEf3z9LXz1zPy5aMabOOsPP2FiNi/QfoBedqMiPhmZ783SZIkqatZvnw5n//853n99de5/fbb+fCHP9yp+y9FDcf/A55v8PoC4JKU0hjgLeDEPP1E4K08/ZI8HxGxNXA0sA1wAHBFHsT0BS4HDgS2BsbneSVJkqRe6xvf+AbTp0/nZz/7Gbvsskun779TA46IGAEcDFyVvw5gH+DWPMt1wOH534flr8mX75vnPwz4VUppaUrpFWAGsGv+mJFSejml9D7wqzyvJEmS1Ctdf/31XHLJJZx22mlMnDixJGXo7GFxfwx8A1g3fz0EeDultDx/PQeoHwh4ODAbIKW0PCLeyfMPBx5rsM2G68xulL5boUJExBRgCsDQoUOprq5u/ztSt7NgwQLPuYrG66t38ryrmLy+ep/mzvn999/PVVddxRtvvMFGG23E5MmT2W+//QrmmTt3LgDl5eUccsghJbuOOi3giIhPA2+klJ6KiHGdtd9CUkqVQCXAFltskcaNK2lx1Mmqq6vxnKtYvL56J8+7isnrq/dp6pxXVVVxySWXsGjRIgDmzp3LRRddxODBgznkkEMAuOuuu7joootYsmTJyvXeeOMN5s6dy4QJEzql/I11Zg3HnsChEXEQMABYD7gUGBwR/fJajhHAq3n+V4FNgTkR0Q9YH5jXIL1ew3WaSpckSZK6tYqKipXBRr0lS5ZwxhlncMYZZzS53uLFi6moqChZwNFpfThSSmellEaklEaRdfqenlKaADwIHJlnOx64I//7zvw1+fLpKaWUpx+dj2I1GhgL/BV4Ahibj3rVP9/HnZ3w1iRJkqSimzVrVsH0iODGG2/kxhtvbPO6naErzMNxJvC1iJhB1kfj6jz9amBInv414JsAKaVngVuA54A/AKeklFbkNSSnAveSjYJ1S55XkiRJ6rZWrFhBRUUF2W/vqxs5ciTjx49n/PjxlJeXN5mnVDq70zgAKaVqoDr/+2WyEaYa51kCHNXE+lOBqQXS7wHu6cCiSpIkSSXz5ptvMn78eB544AHGjRvHX//611WaVZWVlTF16ge3xVOnTmXKlCnN5ulsXaGGQ5IkSVIjjz/+ODvuuCMPP/wwV199NQ8++CCVlZWUl5cTEZSXl1NZWblK34wJEya0mKezlaSGQ5IkSdKqqqqqqKioYNasWQwePJh33nmHkSNH8pe//IUdd9wRyAKKloKH1uTpTAYckiRJUolVVVWt0hTqrbfeok+fPpx11lkrg43uyiZVkiRJUokVGvK2rq6O733veyUqUccx4JAkSZJKrKlha0s5nG1HMeCQJEmSSuiNN96gX7/CPR1KOZxtRzHgkCRJkkrktddeY++99wZg7bXXXmVZqYez7SgGHJIkSVIJ1NbW8t///d/MmTOHBx54gKuvvrpLDWfbURylSpIkSepkL730Evvssw/vvvsu999/P7vtthuQDWlbXV3NuHHjSlvADmQNhyRJklRkVVVVjBo1ij59+jB8+HB23nlnFi5cyPTp01cGGz2VNRySJElSETWeY+O1114D4Ac/+AE77LBDKYvWKazhkCRJkoqo0BwbAFdeeWUJStP5DDgkSZKkIurJc2y0hgGHJEmSVERNzaXRE+bYaA0DDkmSJKmITjjhhNXSesocG61hwCFJkiQVyZIlS7j55pvZYIMN2HTTTXvcHBut4ShVkiRJUpGce+65PPfcc/z+97/ngAMOKHVxSsIaDkmSJKkInnjiCX74wx9ywgkn9NpgAww4JEmSpA63dOlSJk6cyCabbMLFF19c6uKUlE2qJEmSpA523nnn8dxzz3HPPfew/vrrl7o4JWUNhyRJktSBnnzySS644AImTZrEgQceWOrilJwBhyRJktRB6ptSDRs2rNc3papnkypJkiSpg3z3u9/l2Wef5e6772bw4MGlLk6XYMAhSZIkrYGqqioqKiqYNWsWKSX22msvDjrooFIXq8uwSZUkSZLUTlVVVUyZMoXa2lpSSkDWh6OqqqrEJes6DDgkSZKkdqqoqGDRokWrpC1evJiKiooSlajrMeCQJEmS2mnWrFltSu+NDDgkSZKkdho5cmSb0nsjAw5JkiSpnaZOnUpZWdkqaWVlZUydOrVEJep6DDgkSZKkdpowYQKXXXbZytfl5eVUVlYyYcKEEpaqa3FYXEmSJGkN7LDDDgDceuutfPazny1xaboeazgkSZKkNVBTUwPA5ptvXuKSdE0GHJIkSdIaqA84xowZU+KSdE0GHJIkSdIaqKmpYeTIkQwcOLDURemSDDgkSZKkNVBTU2NzqmYYcEiSJEntlFIy4GhBpwUcETEgIv4aEf+IiGcj4tw8fXREPB4RMyLi5ojon6evnb+ekS8f1WBbZ+XpL0TE/g3SD8jTZkTENzvrvUmSJKl3+plhnZgAACAASURBVM9//sPbb79twNGMzqzhWArsk1L6KLA9cEBE7A5cAFySUhoDvAWcmOc/EXgrT78kz0dEbA0cDWwDHABcERF9I6IvcDlwILA1MD7PK0mSJBWFI1S1rNMCjpRZkL9cK38kYB/g1jz9OuDw/O/D8tfky/eNiMjTf5VSWppSegWYAeyaP2aklF5OKb0P/CrPK0mSJBWFAUfLOnXiv7wW4ilgDFltxEvA2yml5XmWOcDw/O/hwGyAlNLyiHgHGJKnP9Zgsw3Xmd0ofbcmyjEFmAIwdOhQqqur1+h9qXtZsGCB51xF4/XVO3neVUxeX13b/fffT9++fZk5cyazZ89ueYVW6GnnvFMDjpTSCmD7iBgM3A5s2Zn7b1COSqASYIsttkjjxo0rRTFUItXV1XjOVSxeX72T513F5PXVtV122WWMGTOGfffdt8O22dPOebMBR0RMa+2GUkontCHv2xHxILAHMDgi+uW1HCOAV/NsrwKbAnMioh+wPjCvQXq9hus0lS5JkiR1OEeoallLfTiGNnp8FvgMWZOoMWT9LY4ANmxpRxExNK/ZICIGAp8EngceBI7Msx0P3JH/fWf+mnz59JRSytOPzkexGg2MBf4KPAGMzUe96k/WsfzOlsolSZIktUddXR0vvviiAUcLmq3hSCkdUv93RJwFLAYmpZQW5mmDgKuBf7ZiXxsD1+X9OPoAt6SUfhcRzwG/iojzgb/n2yN//mVEzADmkwUQpJSejYhbgOeA5cApeVMtIuJU4F6gLzAtpfRsK8olSZIktdns2bNZunSpAUcL2tKH4zRg3/pgAyCltDAivgs8AExtbuWU0jPADgXSXyYbYapx+hLgqCa2NbXQ/lJK9wD3NP82JEmSpDXnCFWt05ZhcdcBNimQvjFQ1jHFkSRJkroHA47WaUvA8Rvgmog4OiJG5Y+jyZo+3Vac4kmSJEldU01NDYMGDWLjjTcudVG6tLY0qfoScBFwLdmkfZD1obga+J+OLZYkSZLUtdWPUJXNTa2mtDrgSCktBr4cEWcAH8mTX2rYp0OSJEnqLWpqathll11KXYwury1NquoNzB8vGGxIkiSpN1q6dCkzZ860/0YrtDrgiIh1I+LXwBvAX4DhefrPIuKc4hRPkiRJ6npefvll6urqDDhaoS01HBeQjVK1I9l8HPV+RzYZoCRJktQrOEJV67Wl0/ihwGdSSk9HRGqQ/jywWccWS5IkSeq66gOOsWPHlrgkXV9bajg2AOYVSF8XWNExxZEkSZK6vpqaGoYOHcoGG2xQ6qJ0eW0JOJ4gq+WoV1/LcTJZnw5JkiSpV6gfElcta0uTqrOBeyNim3y9r+V/7wr8dzEKJ0mSJHVFNTU1HHjggaUuRrfQ6hqOlNJfgI8B/YGXgH2B14A9Ukp/K07xJEmSpK7lvffe49///rc1HK3UlhoOUkr/BI4vUlkkSZKkLu/FF18EHKGqtdoUcABExIeAjWhUO5JSeq6jCiVJkiR1VQ6J2zatDjgiYgfgGmDb+iSyjuP1z307vHSSJElSF1NTU0NE8JGPfKTURekW2lLDMQ14Ffh/wFw+GKVKkiRJ6jVqamoYOXIkAwcOLHVRuoW2BBxjgaNSSjOKVRhJkiSpq3NI3LZpyzwcDwNbFasgkiRJUleXUjLgaKO21HCcCFwVEZsB/wcsa7gwpfRQRxZMkiRJ6mrefPNN3nnnHQOONmhrk6odgP0LLLPTuCRJkno8R6hqu7YEHD8H7ge+j53GJUmS1AsZcLRdWwKOEcBBKaWXilUYSZIkqSurqalhrbXWory8vNRF6Tba0mn8j8BOxSqIJEmS1NXV1NQwZswY+va1N0FrtaWG4w/ARRGxHfBPVu80fltHFkySJEnqahyhqu3aEnBckT+fXWCZncYlSZLUo61YsYIZM2Zw0EEHlboo3UqrA46UUluaX0mSJEk9yuzZs1m6dKk1HG3UqiAiItaKiMcjYotiF0iSJEnqihyhqn1aFXCklJYBo3EoXEmSJPVSBhzt05ZmUtcBJxWrIJIkSVJXVlNTw7rrrsuwYcNKXZRupS2dxgcBEyLik8BTwMKGC1NKp3VkwSRJkqSupKamhrFjxxIRpS5Kt9KWgGMr4G/535s1WmZTK0mSJPVoNTU17LbbbqUuRrfTllGqPlHMgkiSJEld1dKlS5k5cybHHntsqYvS7TjUrSRJktSCl156iZSSHcbbodkajoi4EzgmpfRu/neTUkqHdmjJJEmSpC7CEarar6UmVfP4oH/GfOyrIUmSpF6oPuAYO3ZsiUvS/bQUcFwDLAZIKU0semkkSZKkLqimpoaNNtqIwYMHl7oo3U5LfTgeBD4EEBEvR8SQ9u4oIjaNiAcj4rmIeDYi/l+e/qGI+GNEvJg/b5CnR0T8JCJmRMQzEbFjg20dn+d/MSKOb5C+U0T8M1/nJ+GYZZIkSeoANTU1Nqdqp5YCjrfIZhgHGNWK/M1ZDnw9pbQ1sDtwSkRsDXwTeCClNBZ4IH8NcCAwNn9MAa6ELEAB/hfYDdgV+N/6ICXPc1KD9Q5Yg/JKkiRJgAHHmmgpgPgN8KeIeIWs/8aTeU3Hao+WdpRSej2l9Lf87/eA54HhwGFks5iTPx+e/30YcH3KPAYMjoiNgf2BP6aU5qeU3gL+CByQL1svpfRYSikB1zfYliRJktRmVVVVjBw5krlz53LbbbdRVVVV6iJ1Oy314fgicCdZbcHFZH063lvTnUbEKGAH4HFgWErp9XzRv4H6ueKHA7MbrDYnT2sufU6B9EL7n0JWa8LQoUOprq5u93tR97NgwQLPuYrG66t38ryrmLy+Suf+++/nwgsvZOnSpQC8/fbbnHjiiTz//PPst99+RdtvTzvnzQYceU3B3QAR8VHgorx2ot0iYh2ympPT8+F2V9lfRBR9JKyUUiVQCbDFFlukcePGFXuX6kKqq6vxnKtYvL56J8+7isnrq3QmTpy4Mtiot3TpUm644QbOP//8ou23p53zVvfJSClN6oBgYy2yYKMqpXRbnjw3bw5F/vxGnv4qsGmD1Ufkac2ljyiQLkmSJLXZrFmz2pSuwlodcETEgIg4MyLui4in85GjVj5asX4AVwPPp5QubrDoTqB+pKnjgTsapB+Xj1a1O/BO3vTqXuBTEbFB3ln8U8C9+bJ3I2L3fF/HNdiWJEmS1CrPPvssBx98MFljn9WNHDmyk0vUvbVl1KkryEaQmgn8lqymouGjJXsCxwL75AHL0xFxEPAD4JMR8SKwX/4a4B7gZWAG8AvgywAppfnAd4En8sd5eRp5nqvydV4Cft+G9ydJkqRepKqqilGjRtGnTx9GjRrFFVdcwZQpU9huu+145JFHGD9+PGVlZausU1ZWxtSpU0tU4u6ppU7jDR0OHJVSur89O0opPQw0NS/GvgXyJ+CUJrY1DZhWIP1J4L/aUz5JkiT1HlVVVUyZMoVFixYBUFtbyymnnEJEcNppp/Htb3+bIUOGUFVVRUVFBbNmzWLkyJFMnTqVCRMmlLj03UtbAo5FrDo6lCRJktQtVVRUrAw2Gtp444358Y9/vPL1hAkTDDDWUFuaVP0Q+Jqzd0uSJKm7a6rj9+uvv14wXe3XlhqOTwJ7kU2y9xywrOHClNKhHVkwSZIkqRjmzZvH2muvzZIlS1ZbZofwjteWgOM/wO3FKogkSZJUbE899RSf/exnWbZsGf379+f9999fucwO4cXR6oAjpTSpmAWRJEmSiunqq6/mlFNOYaONNuLRRx+lpqbGDuGdoC01HABExGbA1kAim1Pj5Q4vlSRJkrQGGo4uNWLECDbbbDP+9Kc/sd9++3HTTTex4YYbsssuuxhgdIJWBxwRsR7ZxH2fBeo+SI7fACeu6SzkkiRJUkdoPOTt7NmzmT17Nocddhi/+c1v6Nu3b4lL2Lu0ZZSqS4HtgE8AA/PHvnnaj5tZT5IkSeo0TQ15+/TTTxtslEBbAo5DgckppT+llJblj2pgCtmkgJIkSVLJNTXkbVPpKq62BBwDgXkF0ucDAzqmOJIkSdKa2XDDDQumO+RtabQl4HgE+G5ElNUnRMQg4FzgLx1dMEmSJKmtbrvtNubNm0fjuaod8rZ02hJwfA3YHXg1Iv4UEX8CZudppxejcJIkSVJr3XjjjXzuc59jt912o7KykvLyciKC8vJyKisrHZGqRNoyD8c/I2IsMAHYMk/+JVCVUlpcjMJJkiRJrTFt2jQmT57M3nvvzV133cU666zD5MmTS10s0bZhcacCs1NKP2uU/sWIGJ5S+naHl06SJElqweWXX86pp57K/vvvz2233UZZWVnLK6nTtKVJ1bHA3wuk/w04rmOKI0mSJDWvqqqKUaNG0adPHzbYYANOPfVUDjvsMO644w6DjS6oLTONbwS8WSD9P8CwjimOJEmS1LTGk/q9/fbb9O3blyOOOIK11167xKVTIW2p4ZgF7FUg/b+BOR1THEmSJKlphSb1W7FiBd/5zndKVCK1pC01HD8HLomI/sD0PG1f4PvABR1dMEmSJKkxJ/XrftoyStVFEbEh8BOgf578PnBpSumHxSicJEmSBLBw4ULOPPNMUkoFlzupX9fVliZVpJTOAjYkm3tjd2BoSumbxSiYJEmSBPD444+zww47cPnll3PAAQes1jHcSf26tjYFHAAppYUppSfyx4JiFEqSJEm9V8NRqAYPHswee+zBkiVLmD59Or///e+d1K+baUsfDkmSJKmoGo9C9c4779C3b1++853v8IlPfAKACRMmGGB0I22u4ZAkSZKKpalRqM4///wSlUhryoBDkiRJXYajUPU8BhySJEnqEu68805HoeqBDDgkSZJUcnfccQdHHnkkm222GQMHDlxlmaNQdW8GHJIkSSqpO+64g6OOOooddtiBv/3tb/ziF79wFKoexFGqJEmSVDK//e1vOeqoo9hpp5249957WX/99R2FqoexhkOSJEklcfvtt3PUUUex8847rww21PMYcEiSJKlDNJywb9SoUVRVVTWb54gjjqC8vNxgo4cz4JAkSdIaq5+wr7a2lpQStbW1nHTSSUybNo2FCxeycOFCpk2bxkknnbQyD8Brr73GXXfdVeLSq5gMOCRJkrTGzj777NUm7Fu8eDEnnngi66yzDuussw4nnngiixcvXi1PRUVFZxZVncyAQ5IkSWvk3XffbXZivh/+8If88Ic/bHK5k/r1bAYckiRJard//OMf7Lzzzk0uLy8v54wzzuCMM86gvLy8YB4n9evZDDgkSZLUZiklKisr2W233Vi4cCHf/va3KSsrWyVP4wn7pk6d2mIe9TwGHJIkSWpRw9GlRo4cyZ577snJJ5/M3nvvzd///nfOO+88Kisrm52wb8KECS3mUc/TaRP/RcQ04NPAGyml/8rTPgTcDIwCZgKfSym9FREBXAocBCwCJqaU/pavczzwrXyz56eUrsvTdwKuBQYC9wD/L9UPfyBJkqR2qx+Bqr5T+OzZs5k9ezZHHnkkN998M336ZL9ht2bCPif16306s4bjWuCARmnfBB5IKY0FHshfAxwIjM0fU4ArYWWA8r/AbsCuwP9GxAb5OlcCJzVYr/G+JEmS1A4VFRWrjUAF8MQTT6wMNqSmdNoVklJ6CJjfKPkw4Lr87+uAwxukX58yjwGDI2JjYH/gjyml+Smlt4A/Agfky9ZLKT2W12pc32BbkiRJWgNNjSLl6FJqjU5rUtWEYSml1/O//w0My/8eDsxukG9OntZc+pwC6QVFxBSymhOGDh1KdXV1+9+Bup0FCxZ4zlU0Xl+9k+ddxVTq6+v999+nf//+LF26dLVlG220kdd+EZT6nHe0UgccK6WUUkR0Sp+LlFIlUAmwxRZbpHHjxnXGbtVFVFdX4zlXsXh99U6edxVTKa+vt99+m8985jMsXbqUtdZai2XLlq1cVlZWxkUXXeS1XwQ97Tul1I3u5ubNocif38jTXwU2bZBvRJ7WXPqIAumSJElqh9mzZ7PXXnvxyCOP8Mtf/pJrrrnG0aXULqWu4bgTOB74Qf58R4P0UyPiV2QdxN9JKb0eEfcC32vQUfxTwFkppfkR8W5E7A48DhwHXNaZb0SSJKmn+Oc//8mBBx7Iu+++y+9//3v23XdfAAMMtUun1XBExE3Ao8AWETEnIk4kCzQ+GREvAvvlryEb1vZlYAbwC+DLACml+cB3gSfyx3l5Gnmeq/J1XgJ+3xnvS5IkqbtrOMfGsGHD2HXXXUkp8ec//3llsCG1V6fVcKSUxjexaLWrOB9p6pQmtjMNmFYg/Ungv9akjJIkSb1N4zk23njjDSKCM888k49+9KMlLp16glL34ZAkSVIJFZpjI6XExRdfXKISqacx4JAkSerFnGNDxWbAIUmS1EullFhvvfUKLhs5cmQnl0Y9lQGHJElSL5RS4uyzz+add96hb9++qywrKytj6tSpJSqZehoDDkmSpF4mpcSZZ57JD37wA04++WSuvfZa59hQ0ZR6Hg5JkiR1opQSX//617nkkkv40pe+xE9/+lP69OnDMcccU+qiqYeyhkOSJKmXSClx+umnc8kll/CVr3yFyy+/nD59vB1UcXmFSZIk9WANJ/Vbb731+MlPfsLpp5/OpZdeSkSUunjqBWxSJUmS1EM1ntRvwYIF9OvXj5133tlgQ53GGg5JkqQeqtCkfsuXL6eioqJEJVJvZMAhSZLUQzmpn7oCAw5JkqQe5t///jdf+MIXSCkVXO6kfupMBhySJEk9RF1dHT//+c/Zaqut+M1vfsMRRxxBWVnZKnmc1E+dzYBDkiSpm2o4AtUmm2zCFltswRe/+EW23357nnnmGX7zm99QWVnppH4qKUepkiRJ6oYaj0D1+uuvA3DyySdz5ZVXrhyFasKECQYYKilrOCRJkrqhs88+e7URqAD+8Ic/OOStuhRrOCRJkrqRuro6brnlFkegUrdhDYckSVIXVN8/Y5999mHUqFFUVVVxxx13sP322zN+/HjWWmutgus5ApW6Gms4JEmSupjG/TNqa2s57rjjqKurY+zYsdx4442sWLGCk08+eZVmVY5Apa7IgEOSJKmLKTRDeF1dHUOGDOG5556jX7/sFi4iqKioYNasWYwcOZKpU6faQVxdjgGHJElSF7J8+fIm+2HMnz9/ZbABjkCl7sE+HJIkSZ2s4fwZ9f0z3n33XS655BLGjBnjDOHqUazhkCRJ6kSF+mdMnDiRfv36sWTJEvbaay+OOOIIfv7zn9s/Qz2CAYckSVInKtQ/Y/ny5fTv35+//vWv7LLLLgDstNNO9s9Qj2CTKkmSpA5UqLkUZP0vbrrpJmprawuut3jx4pXBBmT9M2bOnMn06dOZOXOmwYa6LWs4JEmSOkih5lKTJk3i3HPP5aWXXqKuro4+ffpQV1e32rr2z1BPZQ2HJElSKzVVewFZDcbXvva11ZpLLVu2jNraWr71rW/x2GOPce2111JWVrZKHvtnqCcz4JAkSaL5YKJ++ZQpU6itrSWltLL2YqeddmLUqFEMGTKEN954o+C2ly1bxrnnnstuu+3GscceS2VlJeXl5UQE5eXlVFZW2mRKPZZNqiRJUq9XqCnUlClTWLp0Kdtssw3PPPMMX//61wvWXjzzzDMcddRRfPnLX+aiiy4qGHQ0bi7l/BnqTQw4JElSj1dVVdXsiE9nn332asHEokWLOPHEE1vc9ooVK7jxxhsBGD58+CqBC9hcSrJJlSRJ6tEKNYU64YQT+PSnP80hhxzC2LFjm5zZG+COO+7g5ZdfbrJTd8P0CRMm2FxKasSAQ5Ik9WiFai/ef/997r77bmpra9lxxx1Zf/31C65bXl7OoYceyujRo/ne977Xqs7e9cPZ1tXVOZythAGHJEnqoebPn8/3vve9JmsvIoJnnnmGm2++mcsvv7zFYMLaC6l9DDgkSVJJtDQqVHvzXHzxxZx66qlsuummVFRUMGDAgIL7b09TKGsvpLYz4JAkSR2uPUPMTpkyZZV87c3z9a9/nSuvvJLPfe5zPPPMM1x11VU2hZJKyIBDkqQurqNqAjpLoSBg8uTJTJ06lUceeYQ//vGPfPWrXy04KtQpp5zCt7/9bc4880y+9KUvNTly1C677MI222zD8ccfv1oegI033phrrrmGbbfd1qZQUqmllHrUAzgAeAGYAXyzFflTeXl5uuGGG1JjN9xwQyovL08RUTBPS8vNYx7z+Lkxj3nW9DNxww03pLKysgSsfJSVla2SrzV5Ukqprq4uLV68OM2bNy/NmTMn1dTUpKeffjo9+uij6YEHHki/+93v0i233JKuu+66dOWVV6aLL744nX/++amioiJ99atfTSeffHI67rjj0pFHHpkOPvjg9IlPfCLtvvvuabvttktjx45Nw4cPTxtssMEq5WjPIyLSgAEDms1z0EEHpSOPPLLZbfQUDz74YKmLoE7WHc858GRq6n67qQXd8QH0BV4CNgP6A/8Atm5hnXZ9eXfUPwDzmKc35WlueV1dXaqrq+sSea6//vq0bNmytGzZsnT99dcXzHPttdemJUuWpCVLlqRrrrlmtTwDBw5M06ZNS4sWLUqLFi1K06ZNSwMHDiyYZ/HixWnx4sUFt1O/r6VLl6alS5ema6+91jxdPM8111zT4nn/2c9+lubOnZsuv/zy1ZYPGDAgnXvuuemhhx5K9913Xxo6dOgqy+sf66+/fvqf//mf9OUvfzkNGjSoYJ5+/fqlTTfdNA0ZMiSVlZWliCiYr6VHnz590jrrrJM22mijVF5enrbaaqu04447po9//OPpU5/6VDrssMPS+PHj0wknnJBOPfXUJrcTEem+++5LDz/8cNp4440L5hk5cuTK75Ty8vKCecrLy9uUp7vrjjefWjPd8ZzTTMAR2fKeISL2AM5JKe2fvz4LIKX0/WbWWXkA+vXrx0c+8hEAXnrpJZYvX75a/vo8LS1vzTZ6Yp7Ro0cD8MorrzSZZ9SoUQDMnDmz6HlGjhxJSolZs2axYsWK1fL07dt3ZafB5vJsuummAMyePbvJPCNGjABgzpw5TeYZPnw4AK+++mqTeYYNG0ZKiblz51JXV7danj59+jBkyBAA5s2b12Se+iEe3377bQp9ziOCgQMHklJi8eLFqy2v179/fyAbQrIpffv2BSj4niQVT1lZGQMHDmTevHlN5pk0adLKfO19XmuttYiIVpdr1KhR1NbWrpZeXl7OzJkzgdVn9q5/Pw2bOnVUnu6uurqacePGlboY6kTd8ZxHxFMppZ0LLetpM40PB2Y3eD0H2K1xpoiYAkxpnL58+XI22WQTAF544YWCO6jP09Ly1myjJ+apvzF/8cUXm8xTXl4OwIwZM4qepz5IeuWVVwrmWbFiBWPGjGkxz+abbw6w8h9loTxbbrklQMF/svV5tt56a4Amh2hcsWIF22+/PRHB3XffXTBPXV0de+yxBwB33nlnk3nqv6huv/32gnlSSnz6058mIrj55psL5gE48sgjAVbOolvI0UcfTURwww03NJnnuOOO4/rrr29y+fHHH09EcO211zaZZ+LEiQCdkmfSpElEBNOmTWsyz+TJkwG46qqrmswzZUr2VVNZWdlknpNOOgmAX/ziF03mqZ/t+OqrrzZPN8hz0kknERHNnvfTTjuNn/zkJ00uv/DCC+nfvz/nnHMO8+fPX235RhtttPKze/TRRzN37tzV8gwbNozjjjuuyX00lFJi4cKFLFy4sFX5m3PMMcdw4YUXsnTp0pVpa6+9NscccwzV1dVANiP3V7/6Va666ireeOMNNtpoIyZPnszw4cM7PE93t2DBgh7zXtQ6Pe6cN1X10R0fwJHAVQ1eHwv8tIV12lVF21HVvOYxT2/K05XKYh7zdIU8rdlGR/bh6Eyt6d+i1umOzWu0ZrrjOacX9eHYA7i3weuzgLNaWKddX95dqV28eczTXfJ0pbKYxzxdIU9rA4XW3Lx7g99zdcebT62Z7njO6UUBRz/gZWA0H3Qa36aFddr95d1R/wDMY57elKcrlcU85ukKeQwU1JLuePOpNdMdz3lzAUeP6jQOEBEHAT8mG7FqWkppanP5t9hii9RUnwT1TN2xI5a6D6+v3snzrmLy+up9uuM5702dxkkp3QPcU+pySJIkSXKmcUmSJElFZMAhSZIkqWgMOCRJkiQVjQGHJEmSpKLpcaNUtVVEvAc4TFXvsiHwn1IXQj2W11fv5HlXMXl99T7d8ZyXp5SGFlrQ40apaocXmhrCSz1TRDzpOVexeH31Tp53FZPXV+/T0865TaokSZIkFY0BhyRJkqSiMeCAylIXQJ3Oc65i8vrqnTzvKiavr96nR53zXt9pXJIkSVLxWMMhSZIkqWgMOCRJkiQVjQGHJEmSpKIx4FCPExGTImKjUpdDUs8REftExKBSl0NSz9Gbvld6bMAREZMj4paI2KvUZVHniIhjI+JhYDdgUanLo54nIqZExHcjYmCpy6LOERETIuIp4BPAslKXRz2P3yu9T2/8XumRM41HxP7A14DngT0i4v9SSm9FRCSH5eqRIuJQ4Dpg95TSXxst87yr3SIiyL4rJwNnAkuA+4A/l7JcKq6I6AecDlQAB6aUHitxkdSD+L3SO/Xm75UeU8PRqErqSWA/4KfACGBvAG86e7T7gd8DgwEi4isRsSd43tV+EdE/ZZYBfwO2An4OTIqIIaUtnYoppbQceBG4AaiNiP4R8dmI2KTERVM35/dK79Wbv1d6RMAREWcDD0dERUR8MqU0L6X0GvAn4FVg54gYleeN0pVUHSUizsurofsCpJQWAZcCd0XEM8BmwAUR8eOIWKeUZVX3FBH/C9wYERMj4kMppcdTSouBK8l+yNgvInrEd6gyEXF2ROzWIOlRoJbsx4y/AZ8BrouIijy/519t4vdK7+P3Sqbbv6mIOAI4ADiWLLj4UURsDpBSqiP75fv/s3fnCV1bxAAAIABJREFU8VGVZ//HP1cyWVjCTlgVUBQFZJHVujTuuC+PCEqV0kX7aK3VutUNUGyrtfpoa/vT1n1f6i4uiEYRFQQVlE1QFEH2PUBCkrl+f5yTEDCBBGYyk8z3/XrNK3POuc8593DfnMyVe8shaPHQX7vrODPLMbNbgQuAc4B9y465+1vAtcC57n4ZMBw4nCD4EKk2M7sMOJTgS8DRwGgzawfg7oXAg8C5QOdE5VFix8zamdl/gasI/vIIgLuvACYD44Eh7v4z4DLgCjNrGf6OEakWPVdSi54r26vzAQdBF5qX3P1Ld38IeJkKy8G7+3SCCLJ9+BeFaxKTTYmRQuAVoD3BGJ1zdhhod6e7fwng7osJmi471Houpc4KW836AmPdfSJwM8EkBL8vS+PuTwIbgJ+a2QAzG5GQzEqsrAeedfdmwDozu7zCsU8I6sJigPD58gbQqvazKXWVnispSc+VCupMwLGTrlDZwGFlG+5+I9DJzE6pkOYzYCTwl/jlUGKtsjIP+7xOD/8CcA+QB/SucDwanptjZn8D9iYof5FdCicYKAWWEwzmBFgAPA8caGb9KiR/BPhneCy7VjMqMRV2yXwt3LwMuM7MMsPtqLsXAZhZhpn9HWhC0CVC5Ed2/N2l50r9V8X3FT1XKqgzAQdQVkhYCMDd/wkMMLNjKqS9CfhZmDYTuJNg5od93F1BR92xXZmXvXf3LeEDfBZBuY4ysxYV0vYFXiWYAeQYd19Wi3mWOqZif9kKXS7vAzqaWb8wiP0WmAr0Cc/pSvAXyseAbu5+f61mWvZIZX2k3X1j+Fz5gGD83/8L95f9EeM0gr7XpcDQsAuMyI/s2HVbz5X6r6ru+nqubGPJPqTBzE4EfkcQ9X3g7o+G+9OBiLsXmdmvgUvdvWd47BiCmaludHc3sybuviFBH0FqaBdl7u4eNbN0dy8NA41Hgb8CjYCNBEFIrrsvT8wnkGRnwTTKXd39DjNLq/DwTwvrVyZBV4d+7j4sPHY3MMPd7w/rXaaC2bpjJ2Ve9scrN7OIu5eYWRuCLpv7A20InitRgt853ybmE0iyM7OTgBHAV8Bj7r4g3F/2+0rPlXpmJ2WeRvBY0XMllLQtHGYWsWD2qbHA/wHvAyea2ckA7l4aBht7u/u/gc/N7C4zOwu4gqAAPUyrYKMOqGaZR81sb6BhuG8NQV/I1wmCjrRwukEFG/IjYR27GrgbuN3M+pQFsLDtr05AU4JAtqUFs9/tC3QDSsJ0a/SloG6oRpmXfSloTbg2Vfj8eB5YATwENHb3xanwpUBqzsyyzez/ATcCTwJdgN+YWRcIfneFSfVcqSeqUeZRPVe2l7QBhwdzFX8DDHf3NwgGCv9A2M0m/CUyFphgZr2AK4F3CcZq5Lv7HxOTc9ldNSjz8cDBYc+6nwDnAze5e3d3z09M7qUuCOvYV8ABBIuDljVvl0Lwl8iwL+1/AAcuJQhunwYmu/vDici37L5qlvndwL+BfcwszczOI5jZ8Gp3H+DusxOTe6kLwm4wc4Cz3P0V4M/AwQSTnFTso6/nSj1RzTLXc6WCpOpSZWYjgR/cfUK4nUkQ+ae7e7GZPQ284u6PWbCuxs+Ae9x9bYVrRMJfMFIH7GmZh02Um919Y0I+gCQ9M/sdwaxmn7r7M2aW4cHkA5jZQuA6d38i3O5N0OXh8h2eK1keDvCT5LenZW5m/YEF7r4uMZ9Akl2FOjbd3Z+1YLbEQoIuUUVmNoHgi+WnZtaHIMjQc6UO29MyT/XnSlIEHGbWnCAKPBRYCfQN+ztW7GebDTwFXOPuc3c4P71Ck6XUATEocwWWslNh3/zfA2cRTBxxM3ArMN6DedAxszOAf7j7j6ZO1nOl7olBmeu5Iju1kzr2mruvDNPsRfC764Qdu3TruVL3xKDM9VwhSbpUhdHfW8CBwHSCPnE7ag5ku/tcM+sYjtWoON2c1CExKPOU/88rOxeO4ToSuN7dnyOYlrAXcHyFNC8AX5nZFQBmdmz4M03PlbonBmWu54rs1E7q2JAKyQ4C5rn7BjNrb8HMiXqu1FExKHM9V0iCgCOMHAEeCZuZ/gmcaWadwoF9kfD4PkCOmf2eoG9/a9DK4XWRylzizbZNezqNYLV5wnFB84EeZtatQvL/BW4zs2UEzeUVB49LHaEyl3irRh3rER5vDRSa2SXAm0DHMK3qWB2jMo+dWg84LJwZpOxLZ9mXx3AADu5eNuPQLeF2WWR4MHAI0BU4yd3/Vbs5l92lMpd4q6SOlT3kFxAErQeF2+8RzBSTE6bvQ9C177/AwRq8WXeozCXedqOONQi3Twd+Q/C7a0g4qFjqAJV5/NRawGFmh5jZv4HLzCyn7EunBTOE7JiPfwBdzayHmbUxs5YEM1D91N1/6+4/1Fa+ZfepzCXezOxQM3sYuN7MWlSoYxlhkqkEkxAcF/ajnQ10APqHx1cDF7n7UNWxukFlLvG2B3VsYHj8UeBod7/U3ZfUdv6l5lTm8VcrAYeZ/ZTgC+U7BM3X15rZcbDd2goNzKxxuG8R8ALwBcFaDJ3c/Ut3n1Qb+ZU9pzKXeDOzfQi6470LdAJutmDRSDyckciDRZimAfsC14SnFhEsKom7f+/uX9Ry1mU3qcwl3vawjn0THn/e3d+t5azLblKZ147aauHoRzDX9JPAOIIVFs+xYEpTzOwm4HGCPvuY2TnARcDtQE93/7SW8imxozKXeBsIzHH3hwgW+/wcOMXM2gGY2Tgzu59gUoK7gYFmNh1YQ9DHVuoelbnE257UsbcSk2XZQyrzWhDZdZKaM7PBwBp3/yrcNQ/oY2bt3f0HMysAWgKnm9m7BH3ernT3r8P0C4E8d18Yj/xJ7KnMJd7M7BSCvz5Nc/ePCZq4LzGzvd19kZlNJvjr03Az+4QgmL3Rw1VczexcIOIpOgd6XaQyl3hTHUs9KvPEiGkLh5k1M7PXgAnA2WXdZQhWed0APGRm/wX2Ioggc9z9K3c/192/Lhus4+4f64tn3aAyl3gzs3Zm9gpwFcFUyQ+a2fHu/g3wETA0TDoPmAU0Ab4I69iCsvFC7l6gXxB1g8pc4k11LPWozBMr1l2qGhE0W18Svj8CwN3nA5cTLP3+rLufQVCYeWUnmuanrqtU5hJv/YFJ7n64u98M3AVcEB6bBBxkZoPCurQEOMLd10N5HdO0hHWPylziTXUs9ajME2iPAw4zO9/MfmpmTcKR+fcBzxAs9z7QzMrmON/q7u+6+1PhqQcDb5RdRwVZd6jMJd7COpZnZlnARIIZQMqsJmhBA5gCfAbcEbau9QC+M7OGoDpWl6jMJd5Ux1KPyjx5mO/GGmpmZkBb4AkgCnxN8NftS919VZjmUOBs4BN3f6zCuYcRRJWrgAvL+sRJclOZS7ztqo6ZWYa7F5vZ74Du7v6bCufeQbDQUifgfHefV/ufQGpKZS7xpjqWelTmyanGLRxmlu5BlJIDLHH3owlWbV1D8JduANx9MvAtcICZNTWzRuGhb4Ab3P14ffGsG1TmEm/VrGNlf2E6FnguPC833HcV8Et3H6RfEHWDylziTXUs9ajMk1e1Z6kKB/feDKSb2XiCwTSlEKyrYGaXAj+Y2U/d/b3wtH8TTIk6AehkZv3cfTGgxZbqAJW5xFtN65iZZQIrga/M7BbgZDPLc/e1wMYEfQypAZW5xJvqWOpRmSe/arVwWLCI23SCUf0LCAq1GDjSzAZCef+2MeGrzEkEayvMAA4Kv3hKHaAyl3irYR0bG56WDfycoC9uDnBM+AtC6gCVucSb6ljqUZnXDdVt4YgCf3P3RwHMrC/QBbgR+BfQz4Lpwl4EjjKzzmHXmUKCQnw/5jmXeFOZS7zVtI51JFi1/jHgDnf/PDHZlj2gMpd4Ux1LPSrzOqC6YzimA8+ETVYAk4G9PViVMd3MLgmjx45AaVk/fXd/SV886yyVucRbTepY1N0Xu/tUdz9fvyDqLJW5xJvqWOpRmdcB1Qo43H2zuxf5tjUTjiXo+wYwCjjQzF4FngQ+hfJZAqSOUplLvNWwjk0H1bG6TmUu8aY6lnpU5nVDtQeNQ/mgHAfaAC+HuzcC1wI9gYUerMtAOEuA1HEqc4k31bHUozKXeFMdSz0q8+RW02lxo0AGwXoKvcKI8QaCJqoPygpS6hWVucSb6ljqUZlLvKmOpR6VeRKr8cJ/ZjYY+DB8Peju98cjY5I8VOYSb6pjqUdlLvGmOpZ6VObJa3cCjo7AeQQj+4vikitJKipziTfVsdSjMpd4Ux1LPSrz5FXjgENERERERKS6ajRovD5q1qyZd+3aNdHZkFq0adMmGjVqlOhsSD2l+pWaVO4ST6pfqaculvn06dNXuXvryo6lfMDRpk0bpk2bluhsSC3Kz88nLy8v0dmQekr1KzWp3CWeVL9ST10sczP7rqpjNZ2lSkREREREpNoUcIiIiIiISNwo4BARERERkbhJ+TEclSkuLmbx4sUUFhYmOiu1Ljs7m44dO5KRkZHorIiIiIhIPaCAoxKLFy8mJyeHzp07Y2aJzk6tcXdWr17N4sWL6dKlS6KzIyIiIiL1gLpUVaKwsJCWLVumVLABYGa0bNkyJVt2RERERGQ3bVzGga3SulV1WAFHFVIt2CiTqp9bRERERHbTe7fRMIPGVR1Wl6o6YMyYMTRu3Jgrrrhij67TuXNnpk2bRqtWrWKUMxERERFJWeNyoaRol8nUwhEjKzYUcva9H7Fio7ojiYiIiEgKuHQmdD0WLH2nyRRwxMjdE+fzybdruPvt+TG53i233ML+++/PYYcdxrx58wD4+uuvGTJkCP369ePwww9n7ty5ALzyyisMGjSIvn37cswxx7B8+XIAVq9ezXHHHUePHj341a9+hbvHJG8iIiIiIuS0hdKt4KU4VPlFUwFHNQy79yOenfY9AMWlUYbd+xEvfLYYgG7Xv07na17jsSmLcIfHpiyi8zWv0fW68QCs2bSVYfd+xNuzgyCgOi0g06dP56mnnuLzzz9n/PjxfPLJJwBccMEF/P3vf2f69OncfvvtXHTRRQAcdthhfPzxx3z22WcMHz6c2267DYCxY8dy2GGHMWvWLM444wwWLVoU238YEREREUltWTnQbxTzVkXnVJVEYzj20FuXHcGZ//yQDYXFFJc62ZE0GmVFuGpIlQP1d2nSpEmcccYZNGzYEIBTTz2VwsJCPvzwQ4YOHVqerqgo6DO3ePFihg0bxtKlS9m6dWv5lLbvv/8+zz//PAAnnXQSzZs33+08iYiIiIhsp3gLDH8cgE3Fd22pKpkCjmp4+sJDyt9npKdtt92pZSOG9GzLE1MXkRVJo6g0ylk92zJswN4AtGiUuV363Jzs3cpDNBqlWbNmfP755z86dskll3D55Zdz6qmnkp+fz5gxY3brHiIiIiIi1eIO9x8Lew2Gk27faVJ1qYqBVQVFjBjUiRcuOpQRgzqxsmDXo/V35ogjjuDFF19ky5YtbNy4kVdeeYWGDRvSpUsXnn32WSBYpG/GjBkArF+/ng4dOgDw8MMPb3edJ554AoDXX3+dtWvX7lG+REREREQAiJZA99Oh0yG7TKoWjhi497z+5e/Hnd5zj6938MEHM2zYMHr37k1ubi4DBgwA4PHHH+d///d/GTduHMXFxQwfPpzevXszZswYhg4dSvPmzTnqqKNYuHAhAKNHj+acc86hR48e/OQnP2Hvvffe47yJiIiIiJCeAUdUb8kGBRxJ6rrrruO666770f433njjR/tOO+00TjvttB/tb9myJW+99VZc8iciIiIiKWrzGlj2BXQ5AqqxaLS6VImIiIiISPXNfAYeORVWVDkx1XbUwiEiIiIiItXXbyQ07wRtulcruVo4RERERESk+jIaQLcTqp1cAYeIiIiIiFTPu3+GWS/U6BQFHCIiIiIismulxTD3VVg8rUanaQyHiIiIiIjsWnoG/OYDKCms0Wlq4UhRDz30EL/97W8TnQ0RERERqQuiUYiWBtPgZjSo0akKOGJl4zJ48ATYuDxhWSgpKUnYvUVERESkHlswAf6vF6z8qsanKuCIlfdug0Ufw3u3xuRyjzzyCL169aJ3796cd955/PznP+e5554rP964cWMA8vPzOfzwwzn11FPp3j2Ymuyxxx5j4MCB9OnThwsvvJDS0lIAHnzwQfbff38GDhzI5MmTY5JPEREREUkB2U2hY39o0aXGpyZFwGFm35rZF2b2uZlNC/e1MLMJZjY//Nk83G9mdreZLTCzmWZ2cIXrjAzTzzezkTHL4IMnwWePB+9Li4PtGU8H2zfnwpimMO1+8Gjwc0xTuKlVcHzT6iD9vNeD7Wq0gMyaNYtx48bxzjvvMGPGDO66666dpv/000+56667+Oqrr5gzZw5PP/00kydP5vPPPyc9PZ3HH3+cpUuXMnr0aCZPnswHH3zA7Nmzd/dfQ0RERERSzd6D4eyHg3EcNZQUAUfoSHfv4+79w+1rgInuvh8wMdwGOAHYL3xdAPwLggAFGA0MAgYCo8uClLi6eAo0bA3pmcF2JBsatYaT7tjtS77zzjsMHTqUVq2CoKVFixY7TT9w4EC6dAmizYkTJzJ9+nQGDBhAnz59mDhxIt988w1TpkwhLy+P1q1bk5mZybBhw3Y7fyIiIiKSQhZPh8L1u316Ms9SdRqQF75/GMgHrg73P+LuDnxsZs3MrF2YdoK7rwEwswnAEODJPc7JqNe2vU/P2H67RRc48BT49KEg2CjdCgeeCv3OD443arl9+pw2u5WFSCRCNBoFIBqNsnXr1vJjjRo1Kn/v7owcOZI///nP253/4osv7tZ9RURERCSFrVsMDxwP++bBiOd2mbwyyRJwOPCWmTlwr7vfB7Rx96Xh8WVA2Tf1DsD3Fc5dHO6rav+PmNkFBK0jtG7dmvz8/O2ON23alI0bN1Y789nrf8B7/YziXj8jY+Zj2LolFNbg/B0NGjSIc889l1//+te0bNmSNWvW0K5dOz766CNOOOEEXn31VYqLi9m4cSObN2+mpKSkPL+DBw9m+PDh/PrXv6Z169asWbOGgoICevTowe9+9zu+/fZbmjRpwlNPPUXPnj0r/ZyFhYU/+jepTwoKCur155PEUv1KTSp3iSfVr9STTGW+37x/0T5awsq1m5m9m3lKloDjMHdfYma5wAQzm1vxoLt7GIzERBjQ3AfQrVs3z8vL2+74nDlzyMnJqf4FfxaM58gE2HcQADXv3bbNwIEDueGGGzj55JNJT0+nb9++3HrrrZx22mkcdthhDBkyhEaNGpGTk0PDhg2JRCLl+R0wYAB/+tOfOPPMM4lGo2RkZHDPPfcwePBgxo4dy3HHHUezZs3o06cPmZmZlX7O7Oxs+vbtuwefILnl5+ezY5mLxIrqV2pSuUs8qX6lnqQo83G5UFJUvpm7ajK5+adBJAuuX1GjSyVFwOHuS8KfK8zsBYIxGMvNrJ27Lw27TJV9siXAXhVO7xjuW8K2Llhl+/PjnPW4GTlyJCNHbj/u/eOPPy5/f+utwWxYeXl5P6qQw4YNq3SMxqhRoxg1alTsMysiIiIi9culM+HNa2H2SxAtgUgDOPBkOO6WGl8q4YPGzayRmeWUvQeOA74EXgbKvnGPBF4K378MnB/OVjUYWB92vXoTOM7MmoeDxY8L94mIiIiISE3ktA0X+yuBtAwoLYKsJrs1HjkZWjjaAC+YGQT5ecLd3zCzT4BnzOyXwHfA2WH68cCJwAJgMzAKwN3XmNnNwCdhupvKBpCLiIiIiEgNRYuh73lw8EiY8SQU7N4C1wkPONz9G6B3JftXA0dXst+Bi6u41gPAA7HOo4iIiIhIyhn++Lb3ew3Y7cskvEtVsgrimtSTqp9bRERERCqIRuHFi2HhpD2+lAKOSmRnZ7N69eqU+/Lt7qxevZrs7OxEZ0VEREREEmnjUljwNqxfvMeXSniXqmTUsWNHFi9ezMqVKxOdlVqXnZ1Nx44dE50NEREREUmkph3gD3PBo3t8KQUclcjIyKBLly6JzoaIiIiISOKYgaXv8WXUpUpERERERLZxh0dOh5nPxORyCjhERERERGSbwvXB+hvR0phcTl2qRERERERkmwbN4OevxuxyauEQEREREZFtYjxTqwIOERERERHZ5l+Hwvu3x+xyCjhERERERCRQUgR7DYTmnWN2SY3hEBERERGRQCQLTvm/mF5SLRwiIiIiIhIo2hjzSyrgEBERERGRwL0/hZcviekl1aVKREREREQgGoUBv4rp+A1QwCEiIiIiIgBpaXDIRbG/bMyvKCIiIiIidc+qBbB1c8wvq4BDRERERETgmfOCV4ypS5WIiIiIiMCxN0MkM+aXVcAhIiIiIiKw3zFxuay6VImIiIiIpLpFU2DlvLhcWgGHiIiIiEiqe/0qePXyuFxaXapERERERFLd0IegaENcLq2AQ0REREQk1bXoErdLq0uViIiIiEgqm/cGzB0ft8urhUNEREREJJV99A8oKYQDTozL5RVwiIiIiIiksp89D5tWxO3y6lIlIiIiIpLKIpnQtGPcLp80AYeZpZvZZ2b2arjdxcymmNkCM3vazDLD/Vnh9oLweOcK1/hjuH+emR2fmE8iIiIiIlJHzHwWPvg/cI/bLZIm4AAuBeZU2L4VuNPduwJrgV+G+38JrA333xmmw8y6A8OBHsAQ4J9mll5LeRcRERERqXu+yYdZz4NZ3G6RFAGHmXUETgL+E24bcBTwXJjkYeD08P1p4Tbh8aPD9KcBT7l7kbsvBBYAA2vnE4iIiIiI1EGn3wO/eCuut0iKgAP4P+AqIBputwTWuXtJuL0Y6BC+7wB8DxAeXx+mL99fyTkiIiIiIlKZjOy4Xj7hs1SZ2cnACnefbmZ5tXTPC4ALAFq3bk1+fn5t3FaSREFBgcpc4kb1KzWp3CWeVL9ST22Vebsf3qLJhjl8tf9v8bT4jURIeMABHAqcamYnAtlAE+AuoJmZRcJWjI7AkjD9EmAvYLGZRYCmwOoK+8tUPGc77n4fcB9At27dPC8vL9afSZJYfn4+KnOJF9Wv1KRyl3hS/Uo9tVbm738CX2+l3VFHx/U2Ce9S5e5/dPeO7t6ZYND3O+4+AngXOCtMNhJ4KXz/crhNePwdd/dw//BwFqsuwH7A1Fr6GCIiIiIidcsRV8Ko1+J+m2Ro4ajK1cBTZjYO+Ay4P9x/P/ComS0A1hAEKbj7LDN7BpgNlAAXu3tp7WdbRERERETKJFXA4e75QH74/hsqmWXK3QuBoVWcfwtwS/xyKCIiIiJSD0y5D754Bs5/GTIbxvVWCe9SJSIiIiIitaxBM2jSIe7BBiRZC4eIiIiIiNSCXmcHr1qgFg4RERERkVRSshWi0V2nixEFHCIiIiIiqeTTh+Gv+8CmVbVyOwUcIiIiIiKpJPdA6DUcGrasldtpDIeIiIiISCrpfFjwqiVq4RARERERSRWFG6BgZa3eUgGHiIiIiEiqmP0i3N4VVn9da7dUwCEiIiIikir2/gkcdwu02KfWbqkxHCIiIiIiqaJVV2j121q9pVo4RERERERSweY18N1HwToctUgBh4iIiIhIKljwNjw4BFbOrdXbKuAQEREREUkF+x0Lw5+ANj1q9bYawyEiIiIikgoaNIcDTqr126qFQ0RERESkvtu8Bj59BDatqvVbK+AQEREREanvvv0AXr4E1n5b67dWlyoRERERkfruwFPg4qm1uv5GGQUcIiIiIiL1nRm07paQW6tLlYiIiIhIfbZlLbx1A6xakJDbK+AQEREREanPVsyBKf8PCpYn5PbqUiUiIiIiUp91+glcswjSMhJyewUcIiIiIiL1XUaDhN1aXapEREREROqroo3w5Lmw6OOEZUEBh4iIiIhIfbV+CaycC8WbE5YFdakSEREREamvcg+A330K7gnLglo4RERERETqO7OE3VoBh4iIiIhIfVS8Bf75E5j1YkKzoYBDRERERKQ+2rIWmnaE7CYJzUZMAw4zm1idfTsczzazqWY2w8xmmdnYcH8XM5tiZgvM7Gkzywz3Z4XbC8LjnStc64/h/nlmdnwsP5uIiIiISJ3SpD2MeAb2PSqh2YhJwBEGDS2AVmbW3MxahK/OQIddnF4EHOXuvYE+wBAzGwzcCtzp7l2BtcAvw/S/BNaG++8M02Fm3YHhQA9gCPBPM0uPxecTEREREalzSksSnQMgdi0cFwLTgQPCn2Wvl4B/7OxEDxSEmxnhy4GjgOfC/Q8Dp4fvTwu3CY8fbWYW7n/K3YvcfSGwABi45x9NRERERKSOWfc9jGsD+bcmOiexmRbX3e8C7jKzS9z97zU9P2yJmA50Be4BvgbWuXtZWLaYbS0lHYDvw/uWmNl6oGW4v+KKJhXP2fF+FwAXALRu3Zr8/PyaZlnqsIKCApW5xI3qV2pSuUs8qX6lnl2VeWbRGrrPvp3Z3a9ka1bzStPsP/du2nkJq7+YwJcMilNOqyem63C4+9/N7CdA54rXdvdHdnFeKdDHzJoBLxC0lMSNu98H3AfQrVs3z8vLi+ftJMnk5+ejMpd4Uf1KTSp3iSfVr9SzyzJ/9XLYMIefFE+C4+/Y/ti4XCgpKt9stfoT8vJPg0gWXL8iPhnehZgGHGb2KLAv8DlQGu52YKcBRxl3X2dm7wKHAM3MLBK2cnQEloTJlgB7AYvNLAI0BVZX2F+m4jkiIiIiInXbDsEE0+4PXgBH3QBHXAEXTYW7e0NaBKIlEGkAB54Mx92SmDwT+2lx+wOHuvtF7n5J+Prdzk4ws9ZhywZm1gA4FpgDvAucFSYbSTAeBODlcJvw+Dvu7uH+4eEsVl2A/YCpMfxsIiIiIiKJc+lM6Pk/QLiIX6QBHDQU+o6EtgcF+1p0hm4nQbQUItlQWgRZTSCnTaJyHdsWDuBLoC2wtAbntAMeDsdxpAHPuPurZjYbeMrMxgGfAWH4xv3Ao2a2AFi/xB6iAAAgAElEQVRDMDMV7j7LzJ4BZgMlwMVhVy0RERERkbovpy1kNQ3ep2dtCyZO3qFblRn0/wX0HwXTHoSC5bWf1wpiHXC0Amab2VSC6W4BcPdTqzrB3WcCfSvZ/w2VzDLl7oXA0CqudQuQuPYiEREREZF4cIev34FNK3YdTAx/fNv7HYORBIh1wDEmxtcTEREREZFZL8Bzo2DEc7DfscG+JAgmqiPWs1S9F8vriYiIiIgI0P00+J/7oesxic5JjcV6lqqNBLNSAWQSLOK3yd2bxPI+IiIiIiIpYcNSyGgADZrBQWftOn0SinULR07Z+wqrfw+O5T1ERERERFKCOzw7MpgK99fvQlqsJ5itHXHLtQdeBI6P1z1EREREROotMzj2Jjjy2jobbEDsu1SdWWEzjWBdjsJY3kNEREREpN7btBoatYS9635noVjPUnVKhfclwLcE3apERERERGRXNi6j37TL4IOlcNb9cMBJic7RHov1GI5RsbyeiIiIiEhKee82GhcshNbdYO9DEp2bmIh1l6qOwN+BQ8Ndk4BL3X1xLO8jIiIiIlKvjMsNBocDBrByLtzWBSJZcP2KhGZtT8V69MmDwMtA+/D1SrhPRERERESqculMOPBUsPRgO9IADhoKl36R2HzFQKwDjtbu/qC7l4Svh4DWMb6HiIiIiEj9ktMWSovBS4laBEqLIKsJ5LRJdM72WKwHja82s58BT4bb5wCrY3wPEREREZH6Jy0d+o1iuvVmAF9AwfJE5ygmYh1w/IJgDMedBCuOfwj8PMb3EBERERGpX7ZuguGPA7ApPx/y6s9cTLEOOG4CRrr7WgAzawHcThCIiIiIiIhIZZ7+GWQ2gmGPJTonMRfrgKNXWbAB4O5rzKxvjO8hIiIiIlJ/uMP+Q4IZqeqhWAccaWbWfIcWjljfQ0RERESk/jCDQRcmOhdxE+tg4G/AR2b2bLg9FLglxvcQEREREakfigpg4XtBC0daeqJzExcxnRbX3R8BzgSWh68z3f3RWN5DRERERKTemPU8PHUuLPk00TmJm5h3d3L32cDsWF9XRERERKTe6X0uNGkPHfsnOidxo/EVIiIiIiKJkh6BrsckOhdxFeuVxkVEREREpDom3AifP7nrdHWcWjhERERERGpbaTF892EwJW49p4BDRERERKS2pWfALycEgUc9py5VIiIiIiK1qbQYiguD9TcimYnOTdwp4BARERERqU2zXoQ7u8OabxKdk1qhgENEREREpDa12Ae6nw7NOic6J7VCYzhERERERGpTx37BK0UkvIXDzPYys3fNbLaZzTKzS8P9LcxsgpnND382D/ebmd1tZgvMbKaZHVzhWiPD9PPNbGSiPpOIiIiIyI9sXAb3DIblqbVGdsIDDqAE+IO7dwcGAxebWXfgGmCiu+8HTAy3AU4A9gtfFwD/giBAAUYDg4CBwOiyIEVEREREJOHeGQcr58BzoxKdk1qV8C5V7r4UWBq+32hmc4AOwGlAXpjsYSAfuDrc/4i7O/CxmTUzs3Zh2gnuvgbAzCYAQ4D6v5qKiIiIiCSvm3OhtGjb9sq5MKYpRLLg+hWJy1ctSXjAUZGZdQb6AlOANmEwArAMaBO+7wB8X+G0xeG+qvZXdp8LCFpHaN26Nfn5+THJv9QNBQUFKnOJG9Wv1KRyl3hS/aobMovW0H327czufiVbs7Z1srFoCYdYFiUNWpBVtIb0aBGlaVmsajWYr/cdxdZKyra+lXnSBBxm1hj4L/B7d99gZuXH3N3NLGbLMLr7fcB9AN26dfO8vLxYXVrqgPz8fFTmEi+qX6lJ5S7xpPpVR7x6OWyYw0+KJ0HrPrB0Bpz0t+BY05vJnD8B5o2HSDbppVtps3dX2hx/RqWXqm9lnhQBh5llEAQbj7v78+Hu5WbWzt2Xhl2mytqblgB7VTi9Y7hvCdu6YJXtz49nvkVEREQkxY3LhZIK3aWm3R/8NIMhfwlWFO/3c5g/AfqNgv6jYNqDULA8IdlNhIQPGregKeN+YI6731Hh0MtA2UxTI4GXKuw/P5ytajCwPux69SZwnJk1DweLHxfuExERERGJj0tnQs+hYOnBdqQBHDQULp8XBBtlhj8OJ98BbQ8Kfg5/PDH5TYBkaOE4FDgP+MLMPg/3XQv8BXjGzH4JfAecHR4bD5wILAA2A6MA3H2Nmd0MfBKmu6lsALmIiIiISFzktIWsxuClkJYeDA7PagI5bXZ9bopIeMDh7h8AVsXhoytJ78DFVVzrAeCB2OVORERERGQXNq2E/r8Muk5NfyiluktVR8IDDhERERGROmvLOjjxdmjSLtg++Y6dp09BCR/DISIiIiJSZ025F+7qDRvVqlEVtXCIiIiIiOyuXmdDo5Yas7ETCjhERERERHZXiy7Q4leJzkVSU5cqEREREZGaikZhwmhYNT/ROUl6CjhERERERGpq5dxg/MbSGYnOSdJTlyoRERERkZpq0x0unw1ZOYnOScKt2FBIpOVe3ao6roBDRERERKQmSksgPQINWyQ6J0nh7onzSYtkNa7quAIOEREREZGaeP7Xwari//OfROckobpd/zpFJdFgo6plvNEYDhERERGR6nOHNj0gt3uic5JQ6zZvZdJVR3Jqn/ak7STYAAUcIiIiIiLVZwZHXAGHX57onNSKFRsKOfvej1ixsbB8350TvuKnf82nacMMcrIiuAPuXtU1FHCIiIiIiFTHlrXw7QdBK0eKuHvifD5ZuIbT/zGZZeuDoOOI/VtxUd6+lJQ6qwqKGDG4E8Vrlsyp6hoawyEiIiIiUh2fPgoTboCLP4HW+yc6N3G13fgM4If1hQz+80SyImnMG3cC/ToFA+bvPa8/ALcUF26p6loKOEREREREqmPgr6Fl13ofbJSURmnXNJvSqLOyoIjC4ijZGWkc36Mt1510YI2vpy5VIiIiIiI7s3EZPHgCFG6AA05MdG7iwt2Z9cN6ACLpafzisC50zW1MUUmUrEgaRSVRcrIi5OZk1/jaCjhERERERHbmvVvhuw/h5UsSnZO4eXLq95x09wflQcf5h3QmM5LGiEGdeOGiQxkxqBMrC4p269rqUiUiIiIiUplxuVBS4Uv2/DdhTFOIZMH1KxKXrxhZsKKA0qjTrW0OJ/duR6k7++VuWzm9bHwGwLjTe+72fdTCISIiIiKyo2gUjvsTHHgqRBoE+yIN4KChcOkXic1bDBSXRhnxn4/5y+vB5FJNsjM4b3AnMiOxDw8UcIiIiIiI7Gj1fBh/BWz4AUqLIJId/MxqAjltEp273bJu81YemrwQdycjPY2/n3Mwtw/tHff7KuAQERERkdRVNiB843JY9gVMfzjY37ob/OINyGkL/UbBr94OfhYsT2x+qXwxvuqkeXPWMsa+OptZP2wAYGCXFrRsnBX3/GoMh4iIiIikrvdug0UfBwPDo8Xw1ZvQ62zIaAB7Dw5eZU6+I3H5rODuifP55Ns13P32fMadcdBO01zyxGdccMQ+HH1gG/7n4I703bs5+7fJqfSceFHAISIiIiKpZ8cB4dPuD36mZwXBRhLacTG+x6Ys4rEpi0hPM77+UzBdb9drx1MS3bYS+pSFa5iycE35gn21HWyAulSJiIiISCq6dCYccPK27bIB4b9P3gHhk646kv1yG5dvZ2eksW/rRrSu0C3qzIM70DAzneyM4Gt+diSN0/q0Z9LVR9Z6fsso4BARERGR1FK0MRib0SgXsGCa2yQZEL5iQyF/mrKlfOzFmk1bueW12cxfvpHcJtl0b98Eg/LF+A7ZpyUfX3t0+fm3ndWbM/p22LZgX+nuL9gXKwo4RERERCR1rFoAf+8PXzwHm1ZA/1/AryYmzYDwuyfOZ/7aKHe89VX5vienfs+079YCUFhcyojBO1+Mb1VBUUwW7IsVjeEQERERkdTRbG/YJw9yu8NBZ23bn+AB4TuOz3jqk+956pPvyYqkMe36Y8jJzgCqtxhfrBbsixW1cIiIiIhI/VQ25e2672HS32DrZohkwpn3QpvuMb1Vdaaqrcr6zcVceVw3Tu3dvnzsRSTdysdelAUbdVVSBBxm9oCZrTCzLyvsa2FmE8xsfvizebjfzOxuM1tgZjPN7OAK54wM0883s5GJ+CwiIiIikiTKprx9/Wp4ZxzMGx+3W1WcqrYqVQUlr37xA+PGz6GkNEpRSZSMNCiNesLHXsRKsnSpegj4B/BIhX3XABPd/S9mdk24fTVwArBf+BoE/AsYZGYtgNFAf8CB6Wb2sruvrbVPISIiIiKJt+OUt/NeC36+dNH23ahioKqpajPDrlBNKrROlAUlt70xl+Ubihg+YG9O6tWOM/t2pO9ezblr4leMGNSJ/dOW81W0DSt3o7UkGSVFwOHu75tZ5x12nwbkhe8fBvIJAo7TgEfc3YGPzayZmbUL005w9zUAZjYBGAI8Gefsi4iIiEgyuXQm/PdX8O2kYDvSAA48GY67Jea3mnTVkYwbP4dXZ/xA1IOpao/v0ZYVG4o47z9TeOm3h/0oKHlu+hIAPvp6NSf1akeDzHS6t29SPvYiP38V5+clfuxFrCRFwFGFNu6+NHy/DCibo6wD8H2FdIvDfVXtFxEREZFUktMWmnYM3qfHd8rb3CbZ5GRFcIeMdKOoJJiG9vQjOlBUUgoEQcnwf3/Md6s3Uxr18qDkupMOjHl+klEyBxzl3N3NzHedsnrM7ALgAoDWrVuTn58fq0tLHVBQUKAyl7hR/UpNKneJJ9Wv6ksv2UK7pRNY3PEUeixZyNb2J/BD++Np/8ObZH47i1kx/necsrSEr9eVsmpLlCP3ipC3V4T870uYvXAJxzRfTTaQnz8PgE7ZRSyMOhlpUFQcZcPqFcyevp7ZlVy3vpV5Mgccy82snbsvDbtMrQj3LwH2qpCuY7hvCdu6YJXtz6/swu5+H3AfQLdu3TwvL6+yZFJP5efnozKXeFH9Sk0qd4kn1a8amP4QTH6QrkeOgCPfBMq6u4wCtv+iGAsfvT6HtevX8sQlg8jOSAfg/CrSPvn9NEYMzubcgXvzxNRFrNxYSF5e/0rT1rcyT+aA42VgJPCX8OdLFfb/1syeIhg0vj4MSt4E/lQ2mxVwHPDHWs6ziIiIiNSGjcvguVFw1kPQoFmwWvjBI6FDP2h7UNxuWxp1Vm8qIjcnm6uPP4DiaJSsSPouz0u2tTFqU7JMi/sk8BHQzcwWm9kvCQKNY81sPnBMuA0wHvgGWAD8G7gIIBwsfjPwSfi6qWwAuYiIiIjUM2VT3j5/AdwzEDYuB7O4BBsVp7O9+r8zGXbvx2zZWkpamlUr2Eh1SdHC4e7nVHHo6ErSOnBxFdd5AHgghlkTERERkWSy45S3C/ODn/93ENywotJT9lTFNTaGD9iL3h2b0iBTgUZ1JUXAISIiIiJSLZfOhFd+D1+/DaXFcZ3ytqo1NrIiaZx3SOeY36++SoouVSIiIiIi1ZLTFtZ+GwQbMZjytrLVv79ZWcCTUxcx6aojObVPe9It2J+dkcZpfdoz6eojY/BBUocCDhERERFJfkUFwUBxgOadodcw+PVE6DcKCpbv9mXLuktd+exMikuD1ow3Zi3j2he+ID3NyMmKEAWyImnla2zk5mTv+edJIepSJSIiIiLJzR0ePgUi2TBqPJz71LZjJ99R5WkrNhTy2yc/4x/n9t0uSIhGnW43vE5x6bZl3t77aiX7Xfc6WZE0Pvrj0Zx1cEdaNs5iVUERIwZ12m46W6kZBRwiIiIiknwqTnub0wYO/0Mw/a1ZtS9RcbD3xUd1BaBd0wZ8s6qA4lKnd8emzFu+kcLiKJnpaRzfow03nNKdFo0yy6+RytPZxooCDhERERFJPhNvhu8+hBd+A+e/EAwMr6aqBnunm/H1n09k39aNufucvrw3bwUzl6wnK5LG1tIoTRtkqLtUHGgMh4iIiIgkj3G5MKYpfP5YsP3NO8H2uNztklU22LuwuBSASVcdSU52hLQKg737dWrOkxcMBsDMOLV3ewqKShgxqBMvXHQoIwZ1YmVBERJ7auEQERERkeSweQ30PhcK18G8N6BkS5XT3lbsLjXujIMY8/Is3v9qJe9ckUduk2x6d2zK5AWrywd7H9g2h4FdWmx3DXWXqh0KOEREREQkOSz/Ej57DPY9Ei8pophMMkqKsArT3lbVXSqSblx2zP6UlEaJpKfRKCvCiMEa7J0MFHCIiIiISOJsXgNLpsN+x0KXI+D3M2H8lUxpeRo3LR3Ije2mMrhgOVMXruGypz/n4VEDeOKT73nji2VsLY2SFUljSM+2XHfSgduNv1DrRfJQwCEiIiIitaviDFRvj4G5r8JlX0J2U7rdNoOiknPLkw5f0gmWQOYXUzjqgFyaNcokJytCcTRaPthba2MkNwUcIiIiIhIzVa19UdGWN0aT9d1HFL79JxoefSMcchGF6Y0Zds9kLjh8H75bu5m3Zi0rn672hIO2b8HQ2hh1iwIOEREREYkJd+fWN+aWD+b+3TH7sbUkSsfmDYPjN+dipUU0CNM3nPEQzHgIIllkX7+CfVs3okvrRqzZvJWikqpbMNRdqm5RwCEiIiIi1VJZ68WaTVtp0SizysHcBiz8y0kADN58B39Mf5wT0qeSZSVs8UzeKB3A7SXnMRm44+w+ALw5a5laMOoRrcMhIiIiItVScSpagH/mL2DwnyayZWspk646ksFdWpCRHix+kZ2RxuH7teK2s3qVnz92xNE0bNKcDEop9AyyKKZ1q5a8cPUZ293n3vP6M+70nnRv34Rxp/fcrkVD6h61cIiIiIhIpa0XpVFn/oqNnPqPyWytpPUiI924esgBlESj5DbJZt/cxkz5dk352hedWjRkaP+9ys8bsvw/LCudzWOlR/Mcx3IWE+jn6zTgu55TwCEiIiIi5a0Xf3h6Bjed3pMurRoxY/E6zvznh9x6Zi8mf7OKN79cVj62orKpaHc6mNsdVs1jXlYPvjrwj/xl4N48MfUwJm8s5N4EfF6pPQo4REREROq5qmaOKioppfuNb1Ia9fJ9kxas4sjb88mKpDFj9HHcOaw3h3Ztxcwl68rXvahqKtqdDuY2g2GP8dPSEn6aHqk8jdRLGsMhIiIiUoet2FDI2fd+xIoqBla7O39766vysRcXPjqNu8IxGJnpaTTNzmD/No3Jzgi+FmZF0jilVzsmXX0k2RnpnNG3I7k52eWtFy9cdCgjBnViZUFR9TO5aXXwAkjX37tTjUpcREREpA6rOJB73BkH8d3qTawqKKJfpxaVzhwF8PacFVx6zH6YGVOuO5oxL89i/oqC8taLpg0yatZ6sSvv/xVmPAGXzYKsnN3/sFInKeAQERERSVIrNhTypylb6N6v8EcBQFXT0KYZdG7ZiHeuyGPSVUdywaPTmfXDeopLneyMNI7vEYy9KJORnhb/hfT6/RxyD1CwkaIUcIiIiIgkQHVW5L574nzmr41y40uz+NeIgzEzHv34Ox758FvevzKPW16fy2szl1Ia3RZMDO23Fy0aZQKQ2ySbHu2bMGPxuvKZo2o89iIWcg8IXpKSNIZDREREJMZ2Na4CtnWFuuvt+Sxdv6V82tlPF61lnz++RudrXuOxKYtw4I0vl9Hlj+Ppdv3rtGqUSff2TWicnUFOVoSo+3bBxGH7taJ7+ybl99mjsRd7qmAFjL8SNi6rvXtK0lELh4iIiEgNVLdlouK4ioKiEiJpRnZGOvtf9zpbS7d1hXp8yiIeD9e0mH/LiazdtJVWjbPo2aEJH369msLiKJnpxnE92nLjKd3JzcnmhIPaAbuYhjYU99aLnfnuQ/j0URj0m9q9ryQVBRwiIiIiod0JJgAKi0uJutP3pgmVjqsA+H8/68eQnm25/+f9+cVDn2BY+TSz3drm8Jf/Ca519IFtmHpdG6574QuKSqJkpEFx1GkW64HctaHH6bDPT6FB80TnRBJIAYeIiIikhN0NJtydxWu3cPTf3tuuZaIsmMiMpLG1JMroU7oz6aojufHlWbzxZdCFKDsjjaMPyKVL68bs16YxAId1bcXZ/ffiiamLymeF6tWhKd3bNd0uL2WtF/unLeeraJvYD+SOty3roEEzBRuigENERESSW3UChVU/fMeKB88l95dP0qrt3pWmqRhMXDnkAEpKo7RsnAVA12vHU1Jh8buyYCIrksbcm4dw9B3vcXb/jmwoKuGtWcsoLI4SSTNO6tWO6048kGenL6Z/pxbkNsmmZaNMzII1LopKojRvmMkVx3Urv7aZ1agrVH7+Ks7PS8LWi53ZtAru6gPHjoEBv0p0biTBNGhcREQk3jYugwdPgI3Ld+94LNMkmeoMrn7gjY/4w5Lf88DrH1eZZv5zN3LA1ll8/ewNQDDI+vUvlgLB9LHlA7A9CCZ6j32LAbe8XX5+26bZdGjWoHzxuzSDnu2bMOnqIzEz7ji7N+cO6kROVoSikqAbVKl7MONTk2wuPrIrB3UMWiiqM0j73vP6M+70nnRv34Rxp/fcrmtUvZCWDv1HQefDE50TSQL1LuAwsyFmNs/MFpjZNbtKH9m4mFXLFlV5fNUP3zH7lkOrTLOr40qTfGlavHd1UuUnFdMkU15inUb1KzXT7KrcN0/4M9HvPmLz23/areOxTFObqvPvVxZM/P2lD/hs0dry/TO+X8d+142n8zWv0WHmPxhg8+g1cxydr3mNbte/zoPPvcid9z9C4ehWMKYph6x5kTRzBq1+EcY0Je/Znvzng4UATLrqSLq0aki7tHU8nXkTHTM20L9Tc+4e3rf8fv/9359waNeWNClZzTOZN9GSdfTZq1l5i8rJvdrTvX0TVhUUceHBjfi0451ceHDjqoOJo1vR/c1hjDu6ddXBRDWDyD6fXVs7wWgs0zx1LhzyW2jdrep0kjLqVcBhZunAPcAJQHfgHDPrvrNzGlBU/teQynz93+3/YlLT40qTfGl6RuclVX5SMU0y5SXWaVS/aiFNxb9kl5ZAafG2g8WFUFxYfp2Fz1wb7CuzdXP59nZpKh4v2fYFcuFz122fn3WLgq4iZX74jO+fuWJbuX+TD6u/Do65w03Bl+GGMx8iDafhjIdgTFMYlxvc56aWVR/fshZe+wPc3LryNDfnwlMj4LuPgvSVpRnbHJbO3Jb3iTdty9/6JTD137AhaAVg43KY8wpsXhNsb14Di6fB1k3hv80mWL942793tDR47UTF8ly+oZB3560oP7bvtdsHEwfMvYfL/vVful3/OgCLX/0LczPO5dvsczkv8jZp5pwY+YRvs89lbtZIfrr0AYatvIuCC6czLedoSt0A2OKZTGtyDJsP+hlPdQ9aRHKbZHNElxwuSnueATaPC/05Dmibw8m925fnp02TbNZvKebv7d9mQNo8/tF+QpXBxDUNXqbR8k+4psFLVQcT790Giz6G926t+h+ommmarp8dk+vUWprnLwzq5c7SSEoxd991qjrCzA4Bxrj78eH2HwHc/c9VndO/fbpPuyAYxFXs6SzM2JeOv3+btL/uS7YV/yh91I20sesoHN1qp8cBSkY3J2LRH6Up9Ayyx67ioweuZOB3/ybdflwGhZ7BZ+2HkVnwAz02TKr0XiWexqfNhzDw909WmZ8STyMyNviLUenoZlXeK3vsKj7968n0KphcZZ7nNejDlrYD6bPwvio/+9Ruf2DwuTdUmZ9iTydj7BqKtxaRfksb0qrIz9bL5rHsH0PoUvw1GfbjX2hFHuG7jH3YfMgfOOD931aZn9nHPkLPw06laHRLsqzkR2m2eoTMsauZ//kk9n3hlCrz880JjxF5+wY6FX9TxXXS+TZjX5qc/wTN7j+kyvysu3gWLXI7UDy6RRWfK4OssauY+sLd9P/8xirzM6P7lTSd/wKdixdUWe5zs3vR84/vVVkWpW6kV7OufvyvCxmw7Okq68+MVicC0HvV+Crv9UnbYfRZ9t8qj0/daxSH/OrOatXl6OhmVf7bZI9dxdxxg9m3+KtK/40LPYNFGV1Y1+M8en1+U5Vl9dnA2+l30q8oGt2KrErSbPV0MseuYdmi+eTeP6DK/Cw/5y2KnruQzsXfkFlFHfw2Yx/s5DvY64UzqszP9+e8Q6cDDmbr6JaVXqfII2SNXc3nE5+i1/u/qTI/swb+hZzP7qVT8cJKP1fZc7DLVR9QekuHXT7nqqrL5XXnof/f3p3HR1md/R//XMkkIUACJIACEWSRfd8VrVFRcUPqXq1WrdLWStX+rLauVdun9WmrVatWbV1aa23tqlZF6+OK7Mgiyr4oKEvYQiBkvX5/3HeGIQRMgEkyme/79fJlZs6ZzDW5Ls7Mmfvc576FESsf2XftdLyAzK3L6Llzzj5rY1nzwfS6+e1ajbtfVhtrfzqIw0tX7zOe7ZEc1ucMp8eG12t8LneY3+lCBk18/MtrtbIS7m7DJ5VHcKStJ9NKAVhY2ZmJlbfw+k2n0uK+riyoPJIe9nm0fV5lV66pvJl/XzuGyG+P4YHycxjEUsalzqSZlVHiEV6pGMWffBw/T3uCrWNu4/p3KrjTHueklLmkmFPs6Uyr7EPvlE8pGPsgA44bz/JZb9Dl5QtYevIf6DPmLJZOfZGjJl/K4tNfoNfIU1j83t/p9eaVLD/7RboPOZ5Fb/2J3u9cw6rzJnNk/9F88sbT9JlyHWsufpu8nkP4+NXH6Tv9B3xx2Qd06NaPBa8+Tt6Mn1J+9TtkPTZ8n7naeeMqWma1pvKuXFJ871r21Azs9g0UvvVrIqveZck2o9eWd8m0UnZ5Gova5DP4mw9DSWEwaTu8P9MfuowRBS9SRippVDCz7dmMal8ZnKw8/sHdE7zqUiJwx6bg57taBwmuLpIBt22AJ06CL+ZC5d4xE8mA9v1g5ER4+bqanwuDC56BvmcHk8WKmuJJgzsKYPNKeHAIsI94rn4b/v1dWP8RVJTu3Sc1HQ7rD2c9AL8fu+94rp0FbXvAPW33nLhHf08G3NBiFIkAABviSURBVL4BFv0nmNzuK57xD8O0R2D9wppfV9XfUGrt7bffJj8/v6HDqBMzm+3uNc7Am9qE4zxgnLtfFd6+FBjl7tdW6zcRmAgwrEPKsPeuzmFW+kg2txpApy1T2TLqR5TvKiLvw3vpW7mU1HDwXp5yJGWkse34/6G4sIDOH/6M3pXLo+0rU45gh2Wx4yt3AbDjw78wdNtkWvt2Mq2UUk9lo+Uwf9i9ZGblUjTvH+RsX0ylpTKsdCaZVkq5pzA1/RiKBl6JL3udZiWbKOl7EVkLnmRU6TTSrCL49iZ9JCWRLNxSSRt5NcWFBfSecwd5vi7aZ521ZXnmICJVe19PvZ+8kuV08vXR51ppeSwb9mMys3Jh6gMUR1qRVbohGk+ZpzIt/WiKBl5J1oIn2dryKFKPPJasBU8yunQqEauMxtOsoogvckeR3e90igsLGDr7RtpQSHoYz3aaM63tuWQPGE9FeRm5U+4klTJ6VK4i00qpcGNhSi/WDr2JSFoz2sz8X9bmjiF3y9xoPCUeYUb6aLZ0P4+OS59m7RHjSc/pQpv5jzKibHY0F/PSBpJRUcyn3S6m1RH92brmI45Z+guy2UEzK2OXp1FICz7oMonW3Yazff0Kjlj0O8pT0uhX/nE0ntmRIWwafC1lhRvouOJ51nQ9n7arX2FE6XQyrJxdnsbM9FFsajeavPX/ZePA74KlcPjc+xhY8XE0nsUpPXCMDcNvJqNFK7Z9/DpHr/8TWeyMvq5ttGTGoJ/TMqcD2xa/Q5d1k9kRacXQ0lnReD5IH0PRwCsp/Ww2HTZNY9Oga8ha8CQjS6dF/86z0kdS2LwzbXaupHTMDykuLKDrnJ/Qw1dH8/WpdWRTpAOlxwarDotnPk3/HVNo61ujef/C2rFw2P+QmZVL8exnySzdSKSyrMZaTV30bwAqeo2vsTYqUtIoTm8LR42rsR2cwhZH0mLwBRQXFjBgzg85zDdHa3mztWJe1ok0H3YxAJnv3UV2xVaO9DXRWJakdGX10FvJzMql+Xt3sz67P22KlkXjLfUI09NHU9jvMg5b8Ahr259Ieod+ZC/4HaNLp0VzNSd9KM3Lt/Np3lm06n402zesYtTCO2lFUTTnhbRgascradXreIq3baDD3F9TaUafiiXRXM1N7c+GITdQUVrM4R8/wZoOp9F2/bsML50RrcGZ6aPY3GksnT77F1/0/AaRzGzazXuQIeXzo/EsTO1Nqlewtv81tMzNY+vSDzhmzWPRWq6qnWm9biW7Y0+2rZpNl9V/pzi1BYPL5kbjmZ42km2DvkXphiV0+vw11vW9itaL/hyt5apcbMnuS8etM9h29G2U7tzGER/eS5+YcXBFShdKLJPCr9wDQNHcFxi+5RVaURQd5wqsNfOG/SIY5+b/i9zChVRYWo21U77iXTJ3raOsz/k11nJBRhcqzcgddj7FhQXkzfkZvXxltM9S68JHLY+l4/AJAKyd+S/675hCT18VjedjO4ovht1EZlYuq+a8RmoKdN0xf69xpWjglaxfPBVr0Y72nbrXGM/iSC8stwfde/SluLCAdnN+SX8PJv7Fns5c68X8jpfQq2cfAF6e+TGnFL/C2Ir3KSVCOuVMjhxPycjraJ4Kz87bxEU7n2Nc+VvR9lciYykfeQ1pKcbzi0oZ1C6VQSse5aSSN6N9/psxlvX9r+G/n5bxlbwIuc2MZrMf5pTS3X0mp4/lmZZXcXrXNDpnp7JuRyUvryhjXJcIedmpfF5YyrsrtpLfrRWHZ2ewbmsRc5avYcRRnWmX3Zx1BZtYsXIJvXsPICerJevXrWXz6rl07PsVWmVlsXHtcso/nUrWgLNp2TKLzas/InPN2/jgy7GKXXT88Jf0r1y0u3Yi3cjOiLB0yO2kpDWjw9rXaL/seZpV7ohOJj5N60bB8B9Q2qxd9D1715SHOKXsTSotQoqXMzltLJlj9nhbJ+P9n7Az0oadR55K81WTaV6+hZJjb4u2p5dsZsCCe2ix41NSvJyKlAxK07L5vOOpfNblfAAGzL+btLJCWuz4lNTKEpwUCrN6sLD/LZRmtGHA/HvYnDOY7MIltC2YRmplKZUWYWO7Mazoegk9lz7GusNPYlurPvRY9gTtNk7FcCpSMtiUO4xIWRFrjjibzbnDaV60mkHz7yStbHsYTzrlkRYs7XE1Be3HkLFrI70WPQgYrQoXhfEYW9oMYlHv64mU76D78idZ0+kMDl//Nm03TiXVy6iwNAraHcMXh5/IEWteZHn3yymPtKTXogfJ2TI3Gs+2Vn3AK1nS67vsyjyc3I1T6bn0MSLlO8LXlUZZWkvmD7iTHVldydk0h7zP/kl5pAW5m+dE49nY7miW9ZhIduEiOnzxBkuPupquK5+j3cYPon/ngrajWd79CkoztFNVXRQVFdGyZcuGDqNOTjjhhH1OOJJylyp3fxx4HGBYx4hnUEZ6dlvOvvbne/SbvvpFrGApuzyNDMrYkdOXUZOeqda+PNq+PWfAHu3k5zP9ocs4rOBFdnka6ZSzJncMp511brQdYPpDl5FRUBbtk57dNuxz7h7PlVpQGX2u9Oy2HBf7XGGfLuFzZVDGhtyRjK0hnm4x8WzOHVr7eM7aM56UAt8jnhGT/rNXPO1i4pnfNp/xk+7b3WHsyeFzLY0+V3FO793xjDuD4fuIZ/xFVwBXMDzmuaxgdvS5rFUeQyY9w+7VuflMf2gGI2Je+8q2+Uy48sZoO1wZPte8aB9v3Xl3PHwnjGcGaQUVe8QzYeLtwO4lIEE8H0fjKcnpWUNtrNkrnjPP+VpMLu6sdW1EqtXGGZMe3SsXKQWron225g7mmBpqo1NMPF/kjj5ktVH9383+2qv6dIypnTW5Yzh90uN7xZtRsDIay/acAbWK94wJF8KEC6vVDtHnimQfzpBJk2NqB6Y/9H975ersb925u8PZF4TPtTDap7xN993xnPv1sHY+Jr2gfI94zr78BuCGarUzPxpPRZtuDI+t5fx8pj+0aK94xl88saoD8P/CeGZG+6S26hBTyz8KX9cb0VquysX4Sb/YKxex42BRTr8ax7nYeD7LPe6Ax7nqtfzVSY/sFU8kZtwtzu3HxZN+XUNt7B5XSnJ7H3AtV4/nqtgxLOyTXrAo2icltzvfmvidmHDyWXj/qzy76ST+xsmcxxsMa11Kv1NPBOCUsbDw/j9Uay+Jtp9xcvB7Ft7/AM/ujOmTWcIp40/k0phYFn5yP88Wx/RpXsLz143bI96L2NPF1W5Xb9/bJTE/5wPfrHZ790QgqJ3df5ui1r3pN+kZjojp/86v1nDc9pepTM0gvaKUz5v3JH/c+Xs+5bonoOWVpAy/AmY9xWlF66N53P2rYm/vY0ek0vdgztMQaUZqRSmZA8bT/cz76B77O166IdrHKkpp1es4jjn1q9H2XAj6bHwfIs1IqSjlsM49OOy0C+G0C4P2qucqmAapGaRWlNK+Sx848z5yYuPxuXvEkzrwHPqfeevu9nHnh/EsoCIljVSvIKf7sN3x8PUwnjXReFKr4jnzeuD6PeOZMy8aT073YXDmfYyOyQUvbYjGk1JRSsbAcxhx5hW72/l+EM+m6dG/T/sufWgfjedHYTwz9o4n2kdqKxGPcOxPU5twrIWYsQzywvv2qbBZHjPa5pNevHGvtrTiTcxoO4F2+d9m49u/3avPl7WrT+Pss7HdsbTb+H6jiSfZ+jSmWOLRR/WVnH32l/cH295Ju67N+PnIzjw341imbN/FY3VoP5R96lNt/n7Hd3JoeWWwm9Gsp8gvquFE5Iv+tPvnM+/bu722dmyAYVdEn4uanquR9pnDAEawoNHEc9B9JOk0tSVVEWAJcBLBRGMmcLG7L9zXY3r16uWLFy+upwilMWhq3xpI46L6Sk7Ku8ST6iv5JGLO93cOR5M6wuHu5WZ2LTAZSAWe3N9kQ0RERERE4qtJTTgA3P0V4JWGjkNERERERJrYdThERERERKRx0YRDRERERETiRhMOERERERGJG004REREREQkbprUtrgHwsy2A9oXN7m0BQoaOghpslRfyUl5l3hSfSWfRMx5F3dvV1NDk9ul6gAs3teewdI0mdks5VziRfWVnJR3iSfVV/JpajnXkioREREREYkbTThERERERCRuNOGAxxs6AKl3yrnEk+orOSnvEk+qr+TTpHKe9CeNi4iIiIhI/OgIh4iIiIiIxI0mHCIiIiIiEjeacIiIiIiISNxowiFNjpldYWbtGzoOEWk6zOxEM2vR0HGISNORTONKk51wmNlVZvZXMzuuoWOR+mFml5rZ+8AoYGdDxyNNj5lNNLN7zCyzoWOR+mFml5jZbOAEoKyh45GmR+NK8knGcaVJXmnczE4Fvg98AhxtZh+5+xYzM9e2XE2SmY0HngFGu/uMam3KuxwwMzOCsfIq4GZgF/A68F5DxiXxZWYR4HrgVuA0d5/WwCFJE6JxJTkl87jSZI5wVDskNQsYC/wGyAOOB9CHzibtv8CrQGsAM5tkZmNAeZcDZ2bpHigD5gB9gMeAK8wst2Gjk3hy93JgKfAssNrM0s3sXDPr2MChSYLTuJK8knlcaRITDjO7BXjfzG41s5PdfZO7fw68A6wFhpvZkWFfa7hI5VAxs7vDw9CpAO6+E3gAeMnM5gPdgHvN7Ndm1rIhY5XEZGZ3As+Z2eVmluPu0929GHiU4IuMsWbWJMZQCZjZLWY2KuauqcBqgi8z5gBfBZ4xs1vD/sq/1InGleSjcSWQ8C/KzM4BxgGXEkwufmFmPQHcvZLgm+8sgiMe+rY7wZlZlpndC0wEvgZ0r2pz99eBW4CL3f0G4CLgOILJh0itmdkNwBiCDwEnAXeaWQcAd98FPAVcDBzZUDHKoWNmHczs78BNBN88AuDuG4ApwCvAOHf/OnADcKOZ5YbvMSK1onEluWhc2VPCTzgIltD8290/cvengReJuRy8u88mmEF2DL9R+GHDhCmHyC7gJaAjwTk6X6t2ot397v4RgLuvITh02aneo5SEFR41GwLc5e5vAvcQbEJwfVUfd/8zUAgcb2YjzOySBglWDpVtwAvu3hrYambfj2mbSVALawDC8eU1oG39hymJSuNKUtK4EiNhJhz7WQrVDDi26oa73wF0MbOzYvp8CHwD+Hn8IpRDraach2teZ4ffADwM5AODYtorw8dmmdmvgM4E+Rf5UuEGAxXAeoKTOQGWAf8A+pjZsJjufwAeCdua1WugckiFSzL/E968AbjVzNLD25XuXgJgZmlm9hCQTbAkQmQv1d+7NK40ffv4vKJxJUbCTDiAqiRhIQB3fwQYYWZjY/reDXw97JsO3E+w80M3d9ekI3HskfOqn929OBzAFxLk9Qozy4npOwR4mWAHkLHuvq4eY5YEE7teNmbJ5eNAnpkNCyexq4AZwODwMT0IvqF8Fujl7r+v16DloNS0Rtrdt4fjyvsE5//9Nry/6kuMswnWXlcA54dLYET2Un3ptsaVpm9fy/U1ruxmjf2UBjM7HfgewazvfXf/Y3h/KhBx9xIzuxq4zt37h21jCXamusPd3cyy3b2wgV6C1NGX5NzdvdLMUt29Ipxo/BH4BdAC2E4wCWnv7usb5hVIY2fBNso93P0+M0uJGfxTwvpKJ1jqMMzdLwzbHgTmufvvw7pL12Q2cewn51VfXrmZRdy93MwOI1iy2RM4jGBcqSR4z1nVMK9AGjszOwO4BFgCPOvuy8L7q96vNK40MfvJeQrBsKJxJdRoj3CYWcSC3afuAn4NvAucbmZnArh7RTjZ6OzuTwBzzewBMzsPuJEggR721WQjAdQy55Vm1hloHt63mWAt5KsEk46UcLtBTTZkL2GN3Qw8CPzSzAZXTWBh97dOQCuCiWyuBbvfdQd6AeVhv836UJAYapHzqg8F7QivTRWOH/8ANgBPAy3dfU0yfCiQujOzZmb2W+AO4M9AV+DbZtYVgveusKvGlSaiFjmv1Liyp0Y74fBgr+IVwEXu/hrBicKfEy6zCd9E7gLeMLOBwA+AtwjO1Xjb3X/UMJHLgapDzl8BhoYr644BLgPudve+7v52w0QviSCssSVAb4KLg1Yd3q6A4JvIcC3t7wAHriOY3P4FmOLuzzRE3HLgapnzB4EngG5mlmJmlxLsbHizu49w948bJnpJBOEymE+A89z9JeBnwFCCTU5i1+hrXGkiaplzjSsxGtWSKjP7BvC5u78R3k4nmPmnunuZmf0FeMndn7XguhpfBx529y0xvyMSvsFIAjjYnIeHKHe6+/YGeQHS6JnZ9wh2NZvj7n81szQPNh/AzFYCt7r7c+HtQQRLHr5fbVzJ8PAEP2n8DjbnZjYcWObuWxvmFUhjF1Njs939BQt2S9xFsCSqxMzeIPhgOcfMBhNMMjSuJLCDzXmyjyuNYsJhZm0IZoFjgI3AkHC9Y+w622bA88AP3X1RtcenxhyylARwCHKuiaXsV7g2/3rgPIKNI+4B7gVe8WAfdMzsq8Bv3H2vrZM1riSeQ5BzjSuyX/upsf+4+8awzxEE712nVV/SrXEl8RyCnGtcoZEsqQpnf68DfYDZBGviqmsDNHP3RWaWF56rEbvdnCSQQ5DzpP/HK/sXnsN1AnCbu/+NYFvCgcCpMX3+CSwxsxsBzOzk8P8pGlcSzyHIucYV2a/91Ni4mG4DgMXuXmhmHS3YOVHjSoI6BDnXuEIjmHCEM0eAP4SHmR4BzjGzLuGJfZGwvRuQZWbXE6ztbwe6cngiUs4l3mz3tqezCK42T3he0FKgn5n1iun+HeB/zWwdweHy2JPHJUEo5xJvtaixfmF7O2CXmU0CJgN5YV/VWIJRzg+dep9wWLgzSNWHzqoPj+EJOLh71Y5DPw1vV80MhwJHAz2AM9z90fqNXA6Uci7xVkONVQ3yywgmrQPC2+8Q7BSTFfYfTLC07+/AUJ28mTiUc4m3A6ixzPD2BODbBO9d48KTiiUBKOfxU28TDjM72syeAG4ws6yqD50W7BBSPY7fAD3MrJ+ZHWZmuQQ7UB3v7te6++f1FbccOOVc4s3MxpjZM8BtZpYTU2NpYZcZBJsQnBKuo/0Y6AQMD9s3Ade4+/mqscSgnEu8HUSNjQzb/wic5O7Xufva+o5f6k45j796mXCY2fEEHyj/j+Dw9S1mdgrscW2FTDNrGd73KfBPYAHBtRi6uPtH7v5efcQrB085l3gzs24Ey/HeAroA91hw0Ug83JHIg4swzQK6Az8MH1pCcFFJ3P0zd19Qz6HLAVLOJd4OssZWhO3/cPe36jl0OUDKef2oryMcwwj2mv4z8BOCKyx+zYItTTGzu4E/EazZx8y+BlwD/BLo7+5z6ilOOXSUc4m3kcAn7v40wcU+5wJnmVkHADP7iZn9nmBTggeBkWY2G9hMsMZWEo9yLvF2MDX2esOELAdJOa8HkS/vUndmNhrY7O5LwrsWA4PNrKO7f25mRUAuMMHM3iJY8/YDd18e9l8J5Lv7ynjEJ4eeci7xZmZnEXz7NMvdpxEc4p5kZp3d/VMzm0Lw7dNFZjaTYDJ7h4dXcTWzi4GIJ+ke6IlIOZd4U40lH+W8YRzSIxxm1trM/gO8AVxQtVyG4CqvhcDTZvZ34AiCGWSWuy9x94vdfXnVyTruPk0fPBODci7xZmYdzOwl4CaCrZKfMrNT3X0FMBU4P+y6GFgIZAMLwhpbVnW+kLsX6Q0iMSjnEm+qseSjnDesQ72kqgXBYetJ4c9fAXD3pcD3CS79/oK7f5UgmflVDzTtT52olHOJt+HAe+5+nLvfAzwATAzb3gMGmNmosJbWAl9x920QrTFtS5h4lHOJN9VY8lHOG9BBTzjM7DIzO97MssMz8x8H/kpwufeRZla1x3mpu7/l7s+HDx0KvFb1e5TIxKGcS7yFNZZvZhnAmwQ7gFTZRHAEDWA68CFwX3h0rR+w2syag2oskSjnEm+qseSjnDce5gdwDTUzM+Bw4DmgElhO8O32de5eEPYZA1wAzHT3Z2MeeyzBrLIA+FbVmjhp3JRzibcvqzEzS3P3MjP7HtDX3b8d89j7CC601AW4zN0X1/8rkLpSziXeVGPJRzlvnOp8hMPMUj2YpWQBa939JIKrtm4m+KYbAHefAqwCeptZKzNrETatAG5391P1wTMxKOcSb7WssapvmE4G/hY+rn14303AN919lN4gEoNyLvGmGks+ynnjVetdqsKTe+8BUs3sFYKTaSoguK6CmV0HfG5mx7v7O+HDniDYEvUNoIuZDXP3NYAutpQAlHOJt7rWmJmlAxuBJWb2U+BMM8t39y3A9gZ6GVIHyrnEm2os+SjnjV+tjnBYcBG32QRn9S8jSGoZcIKZjYTo+rYfh/9VOYPg2grzgAHhB09JAMq5xFsda+yu8GHNgMsJ1uJmAWPDNwhJAMq5xJtqLPko54mhtkc4KoFfufsfAcxsCNAVuAN4FBhmwXZh/wJONLMjw6UzuwiS+O4hj1ziTTmXeKtrjeURXLX+WeA+d5/bMGHLQVDOJd5UY8lHOU8AtT2HYzbw1/CQFcAUoLMHV2VMNbNJ4ewxD6ioWqfv7v/WB8+EpZxLvNWlxirdfY27z3D3y/QGkbCUc4k31VjyUc4TQK0mHO6+091LfPc1E04mWPsGcAXQx8xeBv4MzIHoLgGSoJRzibc61thsUI0lOuVc4k01lnyU88RQ65PGIXpSjgOHAS+Gd28HbgH6Ays9uC4D4S4BkuCUc4k31VjyUc4l3lRjyUc5b9zqui1uJZBGcD2FgeGM8XaCQ1TvVyVSmhTlXOJNNZZ8lHOJN9VY8lHOG7E6X/jPzEYDH4T/PeXuv49HYNJ4KOcSb6qx5KOcS7ypxpKPct54HciEIw+4lODM/pK4RCWNinIu8aYaSz7KucSbaiz5KOeNV50nHCIiIiIiIrVV13M4REREREREak0TDhERERERiRtNOEREREREJG404RARERERkbjRhENEREREROJGEw4REWkUzOzHZnbjftonmFnf+oxJREQOniYcIiKSKCYAmnCIiCQYXYdDREQajJndCnwD2AB8BswGtgETgXRgGcGFvAYDL4dt24Bzw1/xMNAO2Alc7e6L6jN+ERH5cppwiIhIgzCzYcDTwCggAswBfgs85e6bwj4/Ada7+0Nm9jTwsrv/LWx7E/i2uy81s1HAz9z9xPp/JSIisj+Rhg5ARESS1nHAP919J4CZvRje3z+caLQGWgKTqz/QzFoCxwAvmFnV3Rlxj1hEROpMEw4REWlsngYmuPs8M7scyK+hTwqw1d0H12NcIiJyAHTSuIiINJR3gQlmlmlmWcBZ4f1ZwBdmlgZcEtN/e9iGuxcCK83sfAALDKq/0EVEpLY04RARkQbh7nOAvwDzgFeBmWHT7cB0YAoQexL488APzOxDM+tOMBn5ppnNAxYCZ9dX7CIiUns6aVxEREREROJGRzhERERERCRuNOEQEREREZG40YRDRERERETiRhMOERERERGJG004REREREQkbjThEBERERGRuNGEQ0RERERE4ub/A5CZDShEh7XyAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 936x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Input City name or Province name\n",
    "draw_city_trend(\"Wuhan\", df) # city "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "draw_province_trend(\"Henan Province\", get_province_df(df, \"Henan Province\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Polynomial regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Case1: Overall China"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train dataset: data before 2020-02-09 00:00:00 \n",
      "Test dataset: the last 5 days\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "Sum up all province within China\n",
    "\"\"\"\n",
    "# China total\n",
    "China_df = df[df['date'] > datetime.datetime(2020, 1, 14)] \n",
    "\n",
    "China_total = get_China_total(China_df)\n",
    "\n",
    "Train, Test = split_train_test_by_date(China_total, 5)\n",
    "\n",
    "X_train = Train['Days']\n",
    "y_train = Train['confirmed']\n",
    "X_test =  Test['Days']\n",
    "y_test = Test['confirmed']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>country</th>\n",
       "      <th>countryCode</th>\n",
       "      <th>province</th>\n",
       "      <th>city</th>\n",
       "      <th>confirmed</th>\n",
       "      <th>suspected</th>\n",
       "      <th>cured</th>\n",
       "      <th>dead</th>\n",
       "      <th>Days</th>\n",
       "      <th>net_confirmed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6781</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>中国</td>\n",
       "      <td>CN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>63932</td>\n",
       "      <td>10109</td>\n",
       "      <td>6728</td>\n",
       "      <td>1381</td>\n",
       "      <td>67</td>\n",
       "      <td>55823</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7126</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>中国</td>\n",
       "      <td>CN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>66576</td>\n",
       "      <td>8969</td>\n",
       "      <td>8101</td>\n",
       "      <td>1524</td>\n",
       "      <td>68</td>\n",
       "      <td>56951</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date country countryCode province city  confirmed  suspected  \\\n",
       "6781 2020-02-13      中国          CN      NaN  NaN      63932      10109   \n",
       "7126 2020-02-14      中国          CN      NaN  NaN      66576       8969   \n",
       "\n",
       "      cured  dead  Days  net_confirmed  \n",
       "6781   6728  1381    67          55823  \n",
       "7126   8101  1524    68          56951  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "China_total.tail(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Degree 1:\n",
      "RMSE of training set is 4885.418440669209\n",
      "R2 score of training set is 0.833938703124608\n",
      "MAPE of training set is 18.910553807068474\n",
      "\n",
      "RMSE of test set is 20737.662270793957\n",
      "R2 score of test set is -2.8210251461686626\n",
      "MAPE of test set is 0.3442525765493401\n",
      "---------------------------------------\n",
      "\n",
      "Degree 3:\n",
      "RMSE of training set is 609.8021206028701\n",
      "R2 score of training set is 0.9974127240525348\n",
      "MAPE of training set is 1.4641706809754294\n",
      "\n",
      "RMSE of test set is 4855.305191650914\n",
      "R2 score of test set is 0.7905437284977699\n",
      "MAPE of test set is 0.08278748156088184\n",
      "---------------------------------------\n",
      "\n",
      "Degree 2:\n",
      "RMSE of training set is 714.391310552416\n",
      "R2 score of training set is 0.9964491100126346\n",
      "MAPE of training set is 2.720045922496472\n",
      "\n",
      "RMSE of test set is 3599.6117230878585\n",
      "R2 score of test set is 0.8848744770054365\n",
      "MAPE of test set is 0.06494507933032924\n",
      "---------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
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Vne33x+OMym/eFYVfr/Xxq4AmgeMb+7BI4Y3DhBuGYZRocpvifccOuOoqqFsXhg2D4jCUKGZGRFXXACtE5AgfdA6wGMgAQiOsegHv+u0MoKcfpdUO2OzdXlOAVBGp5TvUU4EpPm6LiLTzo7J6BtIyDMMokYSmeB8yZAjdu3f/gyG55x5YvNj1g9SuHUclA8T6i/WbgNdFpALwE9AHZ7jGici1wHKgm5edBHQBlgJZXhZV3SAijwBzvNzDqrrBb98IvApUBj7wi2EYRokl3BTvaWlpfPih+z/IgAHQqVOclQxgEzAahmEUI4I/m0pKSiI9PZ0zz0zjuOOgWjWYNw/8DPBFRqQJGG3uLMMwjGJEuCnee/SA336Dd94pegOSF2ZEDMMwihlpaWn7f3Wbnu6WRx6BlLBtgfhic2cZhmEUU1ascJMqnnoqDByYt3w8MCNiGIZRDMnOhj593K9uR4+GcsXUb1RM1TIMwyjbPPccTJsGL70ELVrEW5vcsZaIYRhGMWPRIrjrLrjoIrj22nhrExkzIoZhGMWIXbvcV+nVq7tWSHH4Kj0S5s4yDMMoRgwcCAsWQEYGNGiQt3y8sZaIYRhGMWHiRPdV+k03OVdWScCMiGEYRjFg9Wro3RtOOAH+9a94axM9ZkQMwzDiTHY2XH01ZGXBG29ApUrx1ih6rE/EMAwjzjz1lBvO+/LLcOSR8dYmf1hLxDAMI47Mng333QfdusE118Rbm/xjRsQwDCNObN4M3btDo0bw4ovFfzhvOMydZRiGEQdUoV8/+OUX+OQTqFkz3hoVDDMihmEYcWDUKNeJ/uijcNpp8dam4Jg7yzAMo4j5/nv3h8IOHYrv7LzRYkbEMAyjCNm1y/WDVKrkZudNTIy3RgeHubMMwzCKkIED4auv3LQmjRrFW5uDx1oihmEYRURJnNYkL8yIGIZhFAGrVrlpTY4/vmRNa5IXMTUiIvKziHwrIgtEZK4Pqy0iU0VkiV/X8uEiIoNFZKmIfCMirQPp9PLyS0SkVyD8ZJ/+Un9sCRxlbRhGaWfPHrjiCtixA958s2RNa5IXRdES6aCqJ6pq6BfzA4FpqtoKmOb3Ac4HWvmlLzAUnNEBHgDaAm2AB0KGx8tcHziuc+xPxzAMI3/cey/MnAnDh5e8aU3yIh7urK7AKL89Crg4EP6aOmYBNUWkIdAJmKqqG1R1IzAV6OzjqqvqLFVV4LVAWoZhGMWCjAw3N1a/ftCjR7y1KXxibUQUyBSReSLS14c1UNXVfnsNEPrtSiNgReDYlT4sUvjKMOF/QkT6ishcEZm7bt26gzkfwzCMqFm2DHr1gtat4emn461NbIj1EN8zVHWViNQHporI/4KRqqoiojHWAVUdDgwHSElJiXl+hmEYu3a5SRVV4b//LV39IEFi2hJR1VV+vRaYgOvT+M27ovDrtV58FdAkcHhjHxYpvHGYcMMwjLhz++0wd66b3uSww+KtTeyImRERkSoiUi20DaQCC4EMIDTCqhfwrt/OAHr6UVrtgM3e7TUFSBWRWr5DPRWY4uO2iEg7PyqrZyAtwzCMuPHGG/DCC3DHHdC1a7y1iS2xdGc1ACb4UbflgLGqOllE5gDjRORaYDnQzctPAroAS4EsoA+Aqm4QkUeAOV7uYVXd4LdvBF4FKgMf+MUwDCNufP89XH89nH46PPFEvLWJPeIGNpUdUlJSdO7cufFWwzCMUkhWFrRtC2vWuKlNGjfO+5iSgIjMC3ym8Qds7izDMIxCQBVuvBEWLYLJk0uPAckLm/bEMAyjEBg50nWi//OfkJoab22KDjMihmEYB8nXX0P//nDuuXD//fHWpmgxI2IYhnEQbN4Ml10GtWrB66+X/P+D5BfrEzEMwygg2dnQsyf89BPMmAH168dbo6Inz5aIiNwiItX99xsjRGS+iJQhj59hGEZ4Hn3UzY319NNw5pnx1iY+ROPOukZVt+A+8qsFXA08GVOtDMMwijnvvw8PPOBaIgMGxFub+BGNEQn9o6MLMFpVFwXCDMMwyhw//ABXXukmVhw2DKL9k1FGRgYDBgwgIyMjtgoWIdEYkXkikokzIlP8VCbZsVXLMAyjeLJ1K1x8MVSoAG+/DZUrR3dcRkYG3bt3Z8iQIXTv3r3UGJJojMi1uB9HnaKqWUAF/JQkhmEYZYnsbDe1+w8/wLhx0KxZ9MdmZmaSlZUFQFZWFpmZmTHSsmiJxogocDRws9+vApTSSY0NwzBy54knYMIE95OpDh3yd2xqaipJSUkAJCUlkVpKvkjMc+4sERmKc191VNWj/Ey6map6SlEoWNjY3FmGYRSESZPgwguhe3cYMyb6fpAgGRkZZGZmkpqaSlpaWuErGSMizZ0VjRGZr6qtReQrVT3Jh32tqifEQNeYY0bEMIz8snQppKRA8+bw2WfgGxRlhkhGJBp31h4RScS5tRCReljHumEYZYRt21xHemKic2WFMyClcdRVtETzxfpg3F8J64vIY8ClwH0x1cowDKMYoAp9+sB338GUKZCc/GeZ0KirrKwsRo4cSXp6eolyVR0sebZEVPV14B/AE8Bq4GJV/W+sFTMMw4g3//oXjB8Pgwa5yRXDUVpHXUVLNNOetACWqeoQ3O9tzxORmjHXzDAMI45MmQJ33w2XX+5+c5sbpXXUVbRE0yfyFrBPRFoCLwJNgLEx1cowDCPONGrk+kJGjIg8EistLY309HT69+9f5lxZkL/RWf8Adqjqc8GRWiUNG51lGIaRPwpjdFZ3oCfwvg8rX1jKGYZhGCWXaIxIH+BU4DFVXSYizYHR0WYgIoki8pWIvO/3m4vIbBFZKiJvikgFH17R7y/18cmBNO724d+LSKdAeGcftlREBkark2EYhlE4RDM6a7Gq3qyq6X5/maoOykcetwDfBfYHAU+raktgI25uLvx6ow9/2sshIkcDVwDHAJ2BF7xhSgSGAOfjpmXp7mUNwzAOmrL87Ud+iGZ0VisRGS8ii0Xkp9ASTeIi0hi4AHjZ7wvQERjvRUYBF/vtrn4fH3+Ol+8KvKGqu1R1GbAUaOOXpar6k6ruBt7wsoZhGAdFaZ1xNxZE484aCQwF9gIdgNeAMVGm/wzuG5PQF+51gE2qutfvrwQa+e1GwAoAH7/Zy+8Pz3FMbuF/QkT6ishcEZm7bt26KFU3DKOsUta//cgP0RiRyqo6DTeSa7mqPohrXURERC4E1qrqvIPU8aBR1eGqmqKqKfXq1Yu3OoZhFHPK+rcf+SGaaU92iUgCsEREBgCrgKpRHHc6kCYiXXBTx1cHngVqikg539po7NPDr5sAK0WkHFADWB8IDxE8JrdwwzCMAhP69qMkzrhb1ETzncgpuI7xmsAjOGPwlKrOijoTkfbAnap6oYj8F3hLVd8QkWHAN6r6goj0B45T1X4icgXwF1XtJiLH4D5ubAMcCkwDWuF+0fsDcA7OeMwBevjf9+aKfSdiGIaRPyJ9J5JnS0RV5/jNbRTOHw3vAt4QkUeBr4ARPnwEMFpElgIbcCOyUNVFIjIOWIzrl+mvqvsAfMtoCpAIvJKXATEMwwDI1mwSJBpvvpEX0bREpgKXqeomv18LN1qqU8QDiynWEjGMss34xeMZPHsw717xLrUq14q3OiWCg/1ivW7IgACo6kagfmEpZxiGUVTM/GUmV719Fft0H5XK2V++C4NojEi2iDQN7YhIM/wPqgzDMEoK//v9f6Slp1GnXB2O+uoopn4wNd4qlQqiMSL3AjNFZLSIjAE+Ae6OrVqGYRiFx5pta+g8pjPZe7PZMHgDI54fYR8RFhLRTHsyGWgNvIn7KvxkVZ0Sa8UMwzAKg227t3HB2AtYl7WO1HWp7Fy9E7CPCAuLaL4TQVV/58AMvoZhGCWCPfv2cNl/L+PrNV+T0T2Dvd/tZeJLE8nKyrKPCAuJqIyIYRhGSUNVuWHiDUxeOpnhFw6nS6su0Ar7iLCQMSNiGEap5NFPHmXEVyO478z7uP7k6/eHp6WlmfEoRHI1IiJSO9KBqrqh8NUxDMM4eF5d8Cr3f3Q/PU/oycMdHo63OqWaSC2RebihvAI0xf37Q3DTn/wCNI+5doZhGFGSkZFBZmYmddvV5bFlj3HeYefx0kUvIZF+kG4cNLkaEVVtDiAiLwETVHWS3z+fA/8AMQzDiDuh/39kVc+CGtC8RnPGdxtPhcQK8Vat1BPNdyLtQgYEQFU/AE6LnUqGYRj5IzMzk6zyWXAlsAPOXnk21StWj7daZYJojMivInKfiCT75V7g11grZhiGES1tOrRBegqUh0rjK3HJuZfEW6UyQzRGpDtQD5gAvO23u8dSKcMwjGjZvHMzz/z+DOXrlueSHZfw5vNv2uirIiSaqeA3ALeISBVV3V4EOhmGYUTFjj07SHsjjW/XfktG9wzOb3V+vFUqc+TZEhGR00RkMe7HVIjICSLyQsw1MwzDiEDoa/RPl3/KmEvGmAGJE9G4s54GOuF+VYuqfg2cFUulDMMwIpGt2fR+tzcTl0xk2IXDuPzYy+OtUpklql97qeqKHEH7YqCLYRhGnqgqN026ibHfjuXJc56k78l9461SmSaaaU9WiMhpgIpIeeAWvGvLMAyjqPnnjH/ywtwX+Mdp/+CuM+6KtzplnmiMSD/gWaARsArIBPrHUinDMIwQoS/RU1NTWVJ3CY99+hjXt76eJ899Mt6qGUQ3Out33Cc8hmEYRcr+L9Gzsnhp7kvsPn833Y7pxtALhtp0JsWEPI2IiDQHbgKSg/KqagOxDcOIKZmZmWRlZcFRsLvTbprubsroS0aTmJAYb9UMTzQd6+8APwPPAf8JLBERkUoi8qWIfC0ii0TkIR/eXERmi8hSEXlTRCr48Ip+f6mPTw6kdbcP/15EOgXCO/uwpSIyMB/nbRhGCSA1NZWKR1WEv0LCrwk8lfKUzYdVzIimT2Snqg4uQNq7gI6qus13yM8UkQ+A24GnVfUNERkGXAsM9euNqtpSRK4ABgGXi8jRwBXAMcChwIcicrjPYwhwHrASmCMiGaq6uAC6GoZRDKl2XDX0CqXOnjoMPn8w3S7pFm+VjBxEY0SeFZEHcB3qu0KBqjo/0kGqqsA2v1veLwp0BHr48FHAgzgj0tVvA4wHnhfn9OwKvKGqu4BlIrIUaOPllqrqTwAi8oaXNSNiGKWAT5Z/woXpF9Kqbitm9JpBvSr14q2SEYZojMhxwNW4wj/bh4WMQUREJBH3X5KWuFbDj8AmVd3rRVbiRn3h1ysAVHWviGwG6vjwWYFkg8esyBHeNhc9+gJ9AZo2bZqX2oZhxJmZv8yky+tdaFajGdN6TjMDUoyJxohcBhymqrvzm7iq7gNOFJGauAkcj8xvGoWBqg4HhgOkpKRoPHQwDCM6Pl/xOee/fj6Nqzdmeq/pNKjaIN4qGRGIpmN9Ie5vhgVGVTcBM4BTgZoiEjJejXHfnuDXTQB8fA3cVCv7w3Mck1u4YRgllNkrZ9N5TGcaVm3I9F7TOaTqIfFWyciDaIxITeB/IjJFRDJCS14HiUg93wJBRCrjOsC/wxmTS71YL+Bdv53h9/Hx032/SgZwhR+91RxoBXwJzAFa+dFeFXCd73nqZRhG8SAjI4MBAwaQkeFe2zmr5pA6JpX6Veozo9cMDq12aJw1NKIhGnfWAwVMuyEwyveLJADjVPV9PyPwGyLyKPAVMMLLjwBG+47zDTijgKouEpFxuA7zvUB/7yZDRAYAU4BE4BVVXVRAXQ3DKEKCHxGOHDmSR0Y8wiPLH6FuUl1m9JpBo+qN8k7EKBaIq+znEukMwIeq2qHoVIotKSkpOnfu3HirYRhlmgEDBjBkyBC3cwhU7FuRhrUb8nHvj2lawwa/FDdEZJ6qpoSLi+jO8jX+bBGpERPNDMMok6SmppKUlAQNgF5QvWJ1ZvSaYQakBBKNO2sb8K2ITAX2/9lQVW+OmVaGYZRq0tLSeOKVJ7hr8V1UrViVWTfMIrlmcrzVMgpANEbkbb8YhmEUCl+t/opHfnmEOjXq8FHvjzis1mHxVskoINHM4juqKBQxDKNs8MWKLzj/9fOpXrE603pOo2XtlvFWyTgIcjUiIjJOVbuJyLe4L9T/gKoeH1PNDMModcxYNoOL0i+iYbWGTC7Qyw0AACAASURBVOs5zfpASgGRWiK3+vWFRaGIYRilm0lLJvHXcX+lRa0WTL16Kg2rNYy3SkYhEMmIvA+0Bh5V1auLSB/DMEoh4xePp8dbPTi+wfFMuWoKdZLqxFslo5CIZEQqiEgP4DQR+UvOSFW1znbDMPJk1IJRXJNxDac2PpWJPSZSo5J9MVCaiGRE+uF+i1sTuChHnGIjtgzDCEPwn+grG66k/6T+nHvYubxz+TtUqVAl3uoZhUyuRkRVZ+J+JDVXVUfkJmcYhhEiOJ3J8EXD2dN+D2lHpPHmpW9SqVyleKtnxIBohviOEJHT+PM/1l+LoV6GYZRA9v8TvT3sab+HVjtbMf6y8ZRPLB9v1YwYkecsviIyGvg3cAZwil/CzqFiGEbZ5tzzzqXcBeWgPSR+k8igdoPMgJRyovliPQU4WiPN1GgYRpln977dvJX9FntP2cvxWcfzUM+HuLjrxfFWy4gx0RiRhcAhwOoY62IYRgll666t/HXcX5n601Qe6/gYd59xNyISb7WMIiAaI1IXWCwiXwK7QoGqmhYzrQzDKDGs2baGLq934ZvfvmFk15H0PrF3vFUyipBojMiDsVbCMIySyQ/rf6DTmE6s276O97q/x/mtzo+3SkYRE83orI9FpAGuQx3gS1VdG1u1DMMo7sxaOYsLx15IgiQwo9cMTml0St4HGaWOaEZndcP90/wyoBswW0QujXyUYRilmfe+f4+OozpSs1JNvrj2CzMgZZho3Fn3AqeEWh8iUg/4EBgfS8UMwyievDTvJfpN7Efrhq2Z2GMi9avUj7dKRhzJsyUCJORwX62P8jjDMEoRqsqDHz1I3/f70qlFJ2b0mmEGxIjKGEwWkSki0ltEegMTgQ/yOkhEmojIDBFZLCKLROQWH15bRKaKyBK/ruXDRUQGi8hSEflGRFoH0url5ZeISK9A+Mki8q0/ZrDYmELDiAl79u2h05BOPPTxQ5xT+xzeveJdqlaoGm+1jGJAnkZEVf8OvAgc75fhqvqPKNLeC9yhqkcD7YD+InI0MBCYpqqtgGl+H+B8oJVf+gJDwRkd4AGgLdAGeCBkeLzM9YHjOkehl2EY+WDjjo2kPJPC1PVT4RP4fODnfDAxz3qkUUbI1YiISEsROR3ctO+qeruq3g6sE5EWeSWsqqtVdb7f3gp8BzQCugKhX+6OAkKftHYFXlPHLKCmiDQEOgFTVXWDqm4EpgKdfVx1VZ3lv6Z/LZCWYRiFwPe/f0/bl9uycOtCeAeYDjuydpCZmRlv1YxiQqSWyDPAljDhm31c1IhIMnASMBtooKqhr9/XAA38diNgReCwlT4sUvjKMOHh8u8rInNFZO66devyo7phlFkyf8yk7ctt2bRzE48f/jhJPyQBkJSURGpqapy1M4oLkUZnNVDVb3MGquq33ihEhYhUBd4CblXVLcFuC1VVEYn5nFyqOhwYDpCSkmJzgBlGBFSVIXOGcOvkWzm63tFkdM8guWYyR1U9av9/QtLSbMIKwxHJiNSMEFc5msRFpDzOgLwe+BPibyLSUFVXe5dUaOTXKqBJ4PDGPmwV0D5H+Ec+vHEYecMwCsiefXu4+YObGTZvGGlHpDHmkjFUq1gNgLS0NDMexp+I5M6aKyLX5wwUkeuAeXkl7EdKjQC+U9X/C0RlAKERVr2AdwPhPf0orXbAZu/2mgKkikgt36GeCkzxcVtEpJ3Pq2cgLcMw8sn6rPV0GtOJYfOGcdfpd/F2t7f3GxDDyI1ILZFbgQkiciUHjEYKUAG4JIq0TweuBr4VkQU+7B7gSWCciFwLLMd9BQ8wCegCLAWygD4AqrpBRB4B5ni5h1V1g9++EXgV1zL6gCiGHhuG8We+W/cdF6VfxIotKxh18Sh6ntAz3ioZJQTJ6zchItIBONbvLlLV6THXKoakpKTo3Llz462GYRQbJi+dzOXjL6dSuUpMuHwCpzU5Ld4qGcUMEZmnqmF/RhjNBIwzgBmFrpVhGHFFVenzch9eW/UayUnJzLhuBs1qNou3WkYJI5q5swzDKGVs3rmZTsM6MXvzbFgMazLX8PWRX9MszYyIkT9sDizDKGN8veZrUl5KYc6mOTAZ+C/s2GwfEBoFw4yIYZQhXl3wKu1GtCNrT5b7gPAb+4DQODjMnWUYZYCde3dy8wc389L8l+iQ3IH0v6bToGoD+4DQOGjyHJ1V2rDRWUZZY9nGZVz630uZv3o+A08fyCMdH6FcgtUfjeg5qNFZhmGUXCb+MJGrJ1xNtmbz7hXvknaEtTaMwsX6RAyjFLIvex/3Tb+PC9MvpFnNZszrO88MiBETrCViGKWMXzb/QpeXu7Bo2yLOrX0uGddkULl8VNPdGUa+sZaIYZQi3lz4Jkc/dzSLNiyCCe4HUlM/mBpvtYxSjBkRwygFbNm1hV7v9OKKt66g6s6q7p+fX0NWVpZ9/2HEFHNnGUYJ54sVX3DVhKv4edPP3H/W/Zyw5QSu3nU1WWTZ9x9GzDEjYhgllL3Ze3n808d5+OOHaVKjCZ/0/oTTm54OQLn0cvb9h1Ek2HcihlECWbZxGVdNuIrPV3zOVcdfxfPnP0+NSjXirZZRSrHvRAyjFDHmmzHcOPFGRITX//I6PY7rEW+VjDKMGRHDKCGs3b6Wmz64iXGLxnFG0zMYfclokmsmx1sto4xjRsQwijmqythvx3LL5FvYvHMzbbe35fbat5sBMYoFNsTXMIoxKzav4KL0i7hqwlXUlbqUe7kcs5+azVU9riIjIyPe6hmGGRHDKI5kazYvzn2RY144hhk/z+CZTs/QcXlHdq7YCdj3H0bxwYyIYRQzlm5YSsdRHek3sR9tGrXh2xu+5ZZ2t9A5tTNJSfb/D6N4ETMjIiKviMhaEVkYCKstIlNFZIlf1/LhIiKDRWSpiHwjIq0Dx/Ty8ktEpFcg/GQR+dYfM1hEJFbnYhhFwb7sffz7839z3NDjWLBmAS9f9DJTr57KYbUOAyAtLY309HT69+9Penq6ff9hFAti9p2IiJwFbANeU9Vjfdi/gA2q+qSIDARqqepdItIFuAnoArQFnlXVtiJSG5gLpAAKzANOVtWNIvIlcDMwG5gEDFbVD/LSy74TMYoj3/72LddmXMucX+eQdkQaQy8YyqHVDo23WoYBRP5OJGYtEVX9BNiQI7grMMpvjwIuDoS/po5ZQE0RaQh0Aqaq6gZV3QhMBTr7uOqqOkudFXwtkJZhlBg27dzErZNv5cRhJ7Jw5ULuTL6Tdy5/xwyIUWIo6iG+DVR1td9eAzTw242AFQG5lT4sUvjKMOFhEZG+QF+Apk2bHoT6hlE4ZGs2ry54lYEfDuT3rN9JXJDIjik7eEFe4MxaZ5qryigxxK1j3bcgimTOFVUdrqopqppSr169osjSMHLly1VfcuqIU7k241pa1WnFZRsvY+87e2GHjboySh5FbUR+864o/HqtD18FNAnINfZhkcIbhwk3jGLL2u1ruS7jOtq+3JZfNv/Caxe/xsw+M7my45U26soosRS1EckAQiOsegHvBsJ7+lFa7YDN3u01BUgVkVp+JFcqMMXHbRGRdn5UVs9AWoZRrNibvZfBswdz+HOHM+rrUdx56p18P+B7rj7hakTERl0ZJZpYjs5KB9oDdYHfgAeAd4BxQFNgOdBNVTd4Q/A80BnIAvqo6lyfzjXAPT7Zx1R1pA9PAV4FKgMfADdpFCdjo7OMomTGshncPPlmFq5dyHmHnceznZ/lqHpHxVstw8gXkUZn2VTwhhEDvlr9FfdMv4fJSydTbV81+rfsz+NXP459zmSURGwqeMMoIpasX8I/Z/yTNxe9SdXEqpT/qDxbZ25lcIXBnFrzVHNVGaUOm/bEMAqBX7f+Sr/3+3HUkKN474f3uPfMe7nityvY89Ee2GujrozSi7VEDOMg2LBjA4NmDmLwl4PZl72Pfin9uO+s+zik6iFkbMtg7Ctjycqyf50bpRczIoZRALbv3s7g2YMZ9NkgtuzawpXHX8lD7R/aP88VHJjryv51bpRmrGPdMPLB5p2bGTZ3GE9+/CSb9m7ilOqnMKLHCI5rcFy8VTOMmGEd64ZxkPy27Teenf0sQ+YMYcuuLSQsS4DpsGj9Ipa1WMZxaWZEjLKJdawbRgR+2vgTN068kWbPNOPJmU+S2iKVyzZeRvaobFhhHeaGYS0RwwjDN799w6DPBvHGwjdIlER6ndCLv5/+dw6vczgZFTOY+NJE6zA3DMyIGMZ+VJUn05/kxYUvsrzicqpWqMpt7W7jtna30aj6gUmircPcMA5gHetGmWfb7m28/s3rDJo+iGU7lsF2KD+/PCNvHMmVf7ky3uoZRtyxjnXDCMPCtQsZOmcoo78ZzdbdW6mztw5MBr6GPXv28MWRX5gRMYw8MCNilCl27d3F+MXjGTZvGDN/mUnFxIp0O6YbN6TcwNr5a+nxfz3I2mN9HYYRLWZEjDLBTxt/4sW5L/LKglf4Pet3WtRqwVPnPUXvE3tTN6muE2qC9XUYRj6xPhGj1LI+az3jF49n7MKxfLr8UxIkgbQj0rgh5QbOOewcEsRGuBtGNFifiFFm2LZ7G+/+713GLhxL5o+Z7M3eS+OKjTll+yn0a9OPPpf2ibeKhlGqMCNilHh27d3F5KWTGbtwLO99/x479u6gaY2m3N7udhqub8g9197DyqyVLExaSJ0KdcxNZRiFiBkRo0SStSeLJ994kvGLxvNL1V/Yvm87dZPq0ufEPnQ/rjunNTmNBElgwIAB7Mja4Y7xX5ebETGMwsOMiFFi+HHDj0xaMolJSycx7cdp7NE9kACJXyfyQNcHuLf7vZRPLP+HY1JTUxk5cqR9XW4YMcKMSJRcMf4K6ibVpUNyB9ont6dOUp14q1RqycjIIDMzkw7ndqD6cdX3G44f1v8AwOF1Dufo7Ufz9fivYTns27eP3xv8Tvmryv8pLfu63DBii43OioJ92ftIeyONj3/+mO17tgNwfIPj6ZjckQ7NO3BWs7OoWalmLNQtVYSMQ26F+d7svQweN5iBQwayp/EeOAyoAJXKVaJDcge6tOrC+S3Pp0XtFmRkZNC9e/f9LYz09HQzEIYRIyKNzjIjkg/27NvDnF/nMH3ZdGb8PIPPV3zOzr07SZAETjrkJDokd6BD8w6c3uR0alSqUciaFz15Ffr5kQtX6J+VehZfrPiCz1d8zmcrPmP2qtlk7clyB2wElsAFR1zAuEHjSCqfVGD9DMM4OEq1ERGRzsCzQCLwsqo+GUm+ML8T2bV3F7NWzmLGzzOY8fMMZq2cxe59uwFoUasFJzU8idaHtHbrhq2pX6V+vvMozII8P7LR1vSjlbthwA0MGzcMDgWaQO0Ta7Oh3AYAEiWREw85kdObnE7FtRV57h/PsXPtTmthGEYxodR+JyIiicAQ4DxgJTBHRDJUdXFh5xWu4K1YriJnJ5/N2cln8yAPkrUni/+M+w+TFkwioWYC81fPZ/zi8fvTaFSt0X7DsmfFHlbMXcEl51zCX7r+Jdc8QwX0yJEjoyrII8nlRzYzM5OsLNcqiDSqKafc5MzJHH7a4Sxau4hF6/yydhHf1/8e+vuDdkLz2s25/eTbOa3JabRp1IYqFarsT/OMWmdYC8MwSggl2ogAbYClqvoTgIi8AXQFCtWIRFvwfvjBhzzZ98k/umz6nsWCNQv4avVXzF8zn/mr5zPph0lkkw11YMz8MRyy+BCObXwsh9U8jMNqHVjem/pegQrySMNYo5XNbVSTqrJp5yZWbV3Fyi0roTWUO68ce6vvRRoIL9V/iaFDhgIgCM1rNeeYesdw0eEXsWvlLlZ/tZrLO17OxV0vzvV6p6WlmfEwjBJCSTcijYAVgf2VQNucQiLSF+gL0LRp03xnUtBaeUiufXJ72ie33y/3twF/Y/i7w6EeUAuqtanG1l1bmfC/CazLWncgwbrAXcBmSNiZwIJWC7jh/Ruok1SHOpXrULtybeok1aHp6U2p9E4ldm7aSeUKlTnjnDPYvns7iQmJlEsoR6IkIiLAH41D5RqVOaXDKSzdsJRtu7ftX7bu2sq2Jtvo8WwP5i+ZT/VG1Xlm4zP8/fm/s3LLygP9FiFOh2r7qnF4rcPpeGxHjq1/LMfUO4Yj6x75hxYGAL3zffkNwyjGlOg+ERG5FOisqtf5/auBtqo6ILdjCtInUtj9A5Hktu7ayk8bf9q/TPtqGt+t+o5KtSuhlZT1O9azYccGsjU7X+cgyH6jotnKrn27QPI+rlxCORpVa0Sj6o1oXL0xjaq5dXC7YbWGVEiskC99DMMoOZTajnURORV4UFU7+f27AVT1idyOKWjHemF3cB/MyKJszWbLri2sz1rP+h3rWZ/lDMvGnRvZm72Xfdn72Kf79q/DhVUpX4WqFar+YalWsdqfwmpXrm0TFRpGGac0G5FywA/AOcAqYA7QQ1UX5XaMzeJrGIaRP0rt6CxV3SsiA4ApuCG+r0QyIIZhGEbhUqKNCICqTgImxVsPwzCMsog5uw3DMIwCY0bEMAzDKDBmRAzDMIwCY0bEMAzDKDBmRAzDMIwCY0bEMAzDKDAl+mPDgiAi64DlBTy8LvB7KZCLZ97FXS6eeRd3uXjmXdzl4pl3LM4lJ81UtV7YGFW1JcoFmFsa5EqCjnZtip9cSdDRrk3hnEt+FnNnGYZhGAXGjIhhGIZRYMyI5I/hpUQunnkXd7l45l3c5eKZd3GXi2fesTiXqClzHeuGYRhG4WEtEcMwDKPAmBExDMMwCowZEcMwDKPAmBEpRohIFH89B5Ho/lcbbXrRyOYnLS8frY7F/hmM132J17XJT77F/f7F4N7l59qUiXeqWD8AxRER6SQiyTnC/vQwiMhNInJ2FOk9JCL3AWiEUQ4i0kREOni57AhyiSH9IqXnZcuLSMtoZEPxkR58ESknIi2i0LGyiBwblMvlGrYQkbqR9PJyhXpPvGw870v9vNKLBSLSIJp8RSRBRJrlJSsidaIp0ESkbeic85C7SkTC/qI1h9y9IvI3r1+ke1czlF6k59CH1w3KRUizVLxT+SIWXzCW1gVoAnwB1AkTJ4HtZsBi4OhgHJCY45hGwErgc6C3D0sIk3Yz4DPgS+AXoF4u+jUFJgBjvextQOOc+vn9ZOADYCLwFXA9bmqDnGnWBi4FGuVxbRoDb/k0FwGnRdBxIjAV+F/wWua4hocAW4G7gTOBWrmcR6Hek3jeF38u/wVe8/fkskBcYmC7BtAGqJ7HPYlWrpHPMx14Dzg23LUO3OdxfpkIVMlFx0NxU2xc44/503UOXJuPgZph4oLpNQMWAEdGcS5r/HN4Vh73bjowE5gHVIvwXI8GXgC+BnoE4hJyyCZTCt6p/C4FPrAsLsDrwE1+uwVwMTAKOCWH3L+Bh/z28cAjwGTgb0D9gNwY4O/+hk4CTsol31eB2/32E8CNuEKpaxi5v/vt7sAmXzikhElzNHCf377AFwpvhF68gNwUXGF6H9AFqBqISww9hLgC8mFc6/YG4MWcD7KXGw380+8/7V+mf+XU0afzETAeGAb0BY4BrgUqxOqexPO+4Arxx4AqQDdgjs//yBxyU3GG8zrguBzXI3hPopUbCwwCjgDuAh4Mc66hezgaeBSoDzwPnA3cCrTKId8A+B74xD9bFwLVgPMJFL7+WoeuYVPgLOBx4PAc6Q0JPDdHATcD74e51qOBB/xzMh04LMK9u8tvPwX81Ye1DZPe/X67H7Ab90weHibNUvFO5Xcxd1aUiMgRuAdtlw/6F66WtwnIEJHbAuKzgDp++9/ACtwD1QH4h08vBVdLeUpVP8XVUEeLyHk+PtGva+Ne2IU+vctwL+gs4F4ReczL1cJNsPYZgKqm416KncAYEekYOJfKwB7gNy87UVW7AZ8Co0TkGi/XDKgIDAb2AZ2BG0TkDJ9UDRGpiXsQm6vq/eqa0m8BrUWks5dr4N0ax+Be6kd8+CW4QiMLmCQid4R09Om8iKslvu2PfR334FePxT3J532pVZj3RUSqA0nAp6q6XVXHqeopPr0pItLFy7XEGZlX/bn+Dbg45ELx9yQBZ1CjkTsRZwDuUtXvcTXariLSxudXR0QSVFVF5CSgparep6prcQVlH1zt/ysR6RW4f7/hjMEw3PNwI67gvEsPuFuO9Wks9Yc9hTOy9YHZInJV4P4tBCr57Rf8eiZwt4g84tM7FfccPqSqI3AtlxdF5Jgc964BzmC979O5GDgN9z5MEJHQO1rfn9ur/pyG4YxZFpAech952VLxThWIglqfsrbgXAOX4Wpf/8O97KG4Nj48we/XxNUObgfGBuSqAe/imqntgNY58rgZeJY/N5P74Gol6cD8QHgjnPsj1Cy9EVej7IBzI3zmw68C+ukfazCnASOBtvzRJXEq8H+4Gk4l4AgfXgFIw9W4/w/oAfyMq521Ai4HygWuwd84UIP7yOuQDBzvw44Dng7km+KvYWJAxzq4mmoy0BL3gr6FMxZNcW6BbsDQKO5JLdwLk+s98funAydHeV+uAd6M4r70xxWQEe8LrgAYAjTIkc9lHKjh1sPXlnFG4gbcs/aYv5ffAr3zIXcyzu2SELhWDwA3++138bV94CTgVL/dDhgR0PEC4FG/HUrnKFzLrJrf/h1nTB/096MVrsX3L5xLa0YgvTTg4cB+U1wL8wpgZCD8ENy7UQPX2jkzEFfBX/cnw7zP9wIvAa8AXwfCjwVGABX9/qPAQzhX41+Aj334PcDlOd6pU/2xkd6pCkT3TrXAPdvB+xLunWoKHJfXOxUIq0mEd6pAZWNRF8YlecEVks1xhcppgfBLgek5XqCLcIXbAv+iNATOA+aFSTf0EDbC1Y5m+YcjFH4IriBJ8Wme7MNTgdmBdJrhCqHXgGeANB9+PTAuTL6342ok1/uXpwrQlUCBGOaYJv7cpgNfRpA7yb+gFwGTw8QnEfBD41oU08PIdcTVlEbgmvZVgf45ZA4FbsntngTCzsPVxPK8J14+5Fr4w30JxFf359cmj/tSF/iPf3lzvS9AZeA5XIH619D1wRWcMyNc6yP8+c8D5uRXLvCchc73XFxNuSPwYS5p1eaPrtkewAdh5C7FVTCewxmPQ/DGJpQncIq/PmcEwq/MmR7O6L2Pc/N1889rbu9UOb9uiWux/JdAn5XXox+uJfA8Bwz+hXgj7/eb4lxSU/0zGDIcA4DhAbkEr889uEI513eKQEUp0jtFwBBFeqcC968S0b1THcjjncrPYtOeFAARqYAbXLHH788H7lTV6TnkTsI9lDVwfvgtwHOq+rGPFw1zA0RkKPCMOvdCzrjrcA/Br7jC6lZVnZFDpp6qrvPb5YAfcC/MDNyDVRVYo6rv++ZxT69bMu6hfxjXCqjqw9/BNdUJ6SsiWT6tmv6YzcC7qrrbx5fHuYJa4WpbDbzcFi8XckGFRpHMAQbiCtwqwHafb5Jft8QV4Ht92pd6uY242nIikJ3jntzlz6MKsFFV3/b35CKcAdh/T3Culst8fluBCaFzyXFfnsfV+Kr5ezDF65Tzvtzhz6Ua8IuqTsnlvgzAtUyrAIu9XA9cy2EFzlV3Aq4zNBlnaFbh/NqigRE7IrIdV1tuiKv1VgXeVOd6IozcoT6oCs6YrfXxdXGGrC7OAHyGq/Xiz+dNde6q4AigWbjafSOfd01cC209MBdX+aqrqnv8/QulV8HnvTH4PojIHFyBfCgHavCv+/07cIV2ZdxzNQhXgVLcfU0PnrOI1MH1FTyE6+dKwLmS3lPVDSLyIK5FNg3XP3CbvycJOLfj27hHf5dPL8HfuxtVNZMc+HfqatxzlOyv7wNhyoc/vP/+nbo4XJo+PvhOXRAqR3KRDb1Tfw+VD15vxbUCJ/h0mqrq3tzSiQYzInkgIs/ifJh3q+rGHHHlcTWZU3EPSm5yh+AKxWq4gu0PcqGHSUTK+5esOa6zMrf0rgO2AetwBXRu6VXENYtTVfUZEfk3cDjwE+6lfE1VZ/ljTsAZggq4WkpILhHn/vnCyyXiCtoeuIcwrJyXvQnnd90WIb3KODfOCT4uN7kjVfV/IlIJ52IIyZUHxgTkyuE6b9v565Lb+TbA+Y2rqurqHNcmZ97lvKFIxhX6ueV9rb/Pa3EdpiG5isCoQN4VcEbxPFxhdRiuE7oOrpW7z+d3Cu6l3+evd0iuBq4VWU9VV/o0m+IMazNcgf2lT+8cfy5P5lPuKZ9+b/8O5JRNV9UnvOyNOHdVdhi553A1+dqqutyf+1MBuXo44ztGVf/l07saaI0rxENy9YH2wPOqOty/I/v8Pbg5kn4+zeNxBiJneiNU9VkRGeCfkSW4llhIrgFu8EDw2pyJc5s9nkf5cCKuf64CzqWZ23taDmcQewBH55aePyb0Tu2KkF4Srp/nRC+Tm35Hqep3IlJJVXfmzCtqCtqEKQsLrhbxO64puwhX8wjGh4xwyzzkykeZXoVo5PKhX9AX2gr4zm8n4DqTM8kxNDYXuSlAjWCaUciFao8nRJILhB+di1xdH1YumnwDaeaWXu1QWCGec+38XMMccgsC+1/g3C4v41xfjSPIjcN1Wr+JHxmFazl8F7qnPu82XvYlXMEpeci9jCuI6+BqrHmlWRNX+28aRq4trhY/DN/PE0V6tXGVrSYR0hsauI95pZdXvm8T6IuLIr06uOe6PGHeP/7opgqVD3+SK2D5UM7reVQkuRzPV6T0KhZKOVmYhW5pW3AtjGv9dgecy+MzoLMPe8yH5yX3KK7WWVhyj+VD7hy/3RvnIgue3zsc8OPf4V+WwpL7O64mlJfcnbhaZ15yt+N854WZXpsor83tUZ7znfm4him4ARM3+LDTcN+xtPTL80A3HxdJ7rmQXOCeX5Ej74a4grdTFHLDgPP9vkQhG3rWJA+51Cjzjia9F6M8l6FR5js8lG8U+gXzLer3/nFcqygauWjKpUeAcw+6nDzYBEr7gmtuB2ut/XEjnK5NMAAAB2JJREFUWz4DlnGgI71Yy/m4Zv7lDNWsH8HVnpJxfuuEsigXZx1D8SfjRz75/euBVwP70cpdgOszeZlACwnnohybX7lYpFla5ErCex+t3EGVkQebQFlZ8E3OwP5u4OqSIJfzQeFAgdQe59L6FNe5Xqbk4nxtwn4lzIGX/z1c52xUcjniauJqzUtxteqzcYarT0HkYpFmaZErzu99QeQKshRKAVvWFpwr4p2SLudlvwE+N7n45U0OQ4EbfBFuaGaecvi+I799OAe+ML+rIHKxSLO0yEW4z8X6vc9P+RDV+RZWQqV14UBNsg1wnd+uT455koq7XBjZ6/12Z/48RUiZkitGOobuX1v8HF/RyPHHKTBCAxDaAZf47VCrJSq5/MiWNbkIsn96/4q7XM53oKBL3Avp4rgQxoWAG0N+UUmSy0M2rSzLFVMdC/o8VObPk3tO488FZVRysUiztMjlIRvtfSkWcoW1lMPYj4jUA7ZqjjHTInIy8KuqvlcS5KKUzSiLcv/f3rmGSlWFYfh5ye5ldAEz7WKhhpDRTYQiMSqyfhSFmUQURP0pSrqAUUQhQVEURCVEQQTdjJSCyDKTgsxILI1uGklhHisiNIoQ8evHt06NRz2zzzjjmdm+Dyxmz97vXrPWd87Z39l71npXl7dxqL8PE8lRcNuATZLmR8QvSv+vjRGxqJw6XlJTXURsb3edddFVjE3Vn8uw6tpOJzJTrxZy6ORPwFW7ONbvpTOi23V16otjM6juPXIm+zWkKeFNe6Irr22tsy66OsVm4O/UnpZhv3B3SyHHVC8lR86sIS24z2o4Po6cVNXVujr1xbEZVHcZO3o8TQPeB44t748lnQUq6cp2W+usi65OsenItXNvXqi7uZCeP40Tjh4gLSueIi1NFpMWy12tq1NfHJtBdVOB24umf8bzIspCVqTP1JlVdWW7rXXWRVen2HTi2un1RABJ40nbhr7iIUVEPED+sUKa9B0E9HWzLiI+qktfHJtBdRvJcf4fSpoUxXSSTDAnS7qStCzZUkUXEauU64y0rc666OoUm4hYRQfY5w0YJY0hM/Zm0jX1H3K26oKIWFc0m0nTuoe6WHc+6ZNTh744Ns11W4AfSSO+DeRaG9tJq/SDyZnJj1TQzSRNAhe1sc666OoUm5kR8RUdwEkkXTj/joh7yuiGieT4+xGkffQp5HPq47tZFxGP1aUvjk1LugNIH62XyDuVTVV0ETFrkNi0VGdddHWKTUTMolN04hlZLxVyXYP5A/ZNJk3Z5pX36nZdnfri2LSsm1veH1hVVyE2Q66zLro6xabxeLvLsF/Eh7uQ1tNvk86gUxr2jyQtlE/sBV0vtNGx6ajuCHJlvLFD0XWizrroeqGNQ+lLp8o+/zgLQNJo0uxuAnl7+Bq5ANAjEXFqr+h6oY2OTffpeqGNjk17+tIROp2leqWQY62nk0toriNvB3fy2u92XS+00bHpPl0vtNGxaU9f2l18J7ILlGsR7xf/D5XrSV0vtNGx6T5dL7TRsdlzXbtwEjHGGNMynmxojDGmZZxEjDHGtIyTiDHGmJZxEjHGGNMyTiLGNEHS8ZKWSfpa0leSbm84dpSkJZLWldcjy/5rJa2R9KWk5SqGiuXYJZK+k/S9pLm7+cwXJK2XtFrSWkkvShpboa1zJB3Sjn4bUwUnEWOasw24MyImkZbbt0iaVI7NBZZGxHhyHZD+pLAemBYRpwHzyHH7SNoPeBqYQa6PPruhroHcHRGnk35InwMfSDqgSVvnkHMGjNkrOIkY04SI6Itiox0RfwLfkOt+AFxOOqZSXq8ouuUR8UfZvwLov4uYAnwfET9ExFbg1VLHYJ8fEfEEORt5BoCk+ZJWljujB8u+24DjgGWSlpV9F0v6RNIqSa9LOmzPomHMjjiJGDMEJJ0EnAF8WnaNioi+sr0JGLWL024E3inbY0ir93428H9CasYqoN/G4t6IOJs025smaXJEPEk6u06PiOmSjgHuI2cunwmsBO6o+FnGVGLEcDfAmF6h/Bf/BjAnIrYMPB4RISkGnDOdTCLntaMJDdtXS7qZ/BseTT4aWzNAP7Xs/1gSpD34J21ohzH/4SRiTAUk7U8mkJciYmHDoV8kjY6IvmKE92vDOZOB54AZEfF72f0zuSZIP2PLviqcASyVNA64CzgnIv6Q9AK54uFOzQaWRMTsivUbM2T8OMuYJij/jX8e+CYiHh9w+C3g+rJ9PfBmOecEYCFwXUSsbdB/BoyXNK58SX5NqWPQzy/fd4wmlzwdCfwFbJY0ivI9SeFP4PCyvQI4V7m8K5IOlTShes+NaY6TiDHNOZe02r5A0helXFqOPQxcJGkdcGF5D3A/cDTwTNGvBIiIbcCtwLvkF/QLYvfLlj4qaTWwFjiH/K5ja0SsJkdrfQu8DHzccM6zwGJJyyLiN+AG4BVJa8hHWZ23Bjf7FDZgNMYY0zK+EzHGGNMyTiLGGGNaxknEGGNMyziJGGOMaRknEWOMMS3jJGKMMaZlnESMMca0zL/dNsBoe12O1QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Model selection:\n",
    "  find optimal degree level\n",
    "  Then draw plot using the optimal degree\n",
    "\"\"\"\n",
    "# select the best degree \n",
    "create_polynomial_regression_model(1, \"Overall\", China_total, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(3, \"Overall\", China_total , X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(2, \"Overall\", China_total, X_train, X_test, y_train, y_test, draw_plot = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**based on the result above, we can clearly see that degree = 2 gives us best estimation. So now we use degree = 2 to predict the next 4 days**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🍎Forescast the next 4 days\n",
      "Degree 2:\n",
      "RMSE of training set is 1693.06827399849\n",
      "R2 score of training set is 0.9931917578952363\n",
      "MAPE of training set is 2.5405856366508424\n",
      "\n",
      "---------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"\\n🍎Forescast the next 4 days\")\n",
    "forecast_next_4_days(2, \"Overall\", China_total)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Case2: Each Province"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train dataset: data before 2020-02-09 00:00:00 \n",
      "Test dataset: the last 5 days\n",
      "Degree 1:\n",
      "RMSE of training set is 3823.804102996427\n",
      "R2 score of training set is 0.7997137255985216\n",
      "MAPE of training set is 14.672227135174468\n",
      "\n",
      "RMSE of test set is 19872.73019138965\n",
      "R2 score of test set is -2.8779558818062294\n",
      "MAPE of test set is 0.41111751038441685\n",
      "---------------------------------------\n",
      "\n",
      "Degree 3:\n",
      "RMSE of training set is 461.5990719915726\n",
      "R2 score of training set is 0.9970812978872243\n",
      "MAPE of training set is 0.8032793738850621\n",
      "\n",
      "RMSE of test set is 3912.173126848434\n",
      "R2 score of test set is 0.8497121323473371\n",
      "MAPE of test set is 0.09106538323142754\n",
      "---------------------------------------\n",
      "\n",
      "Degree 2:\n",
      "RMSE of training set is 757.9536103946997\n",
      "R2 score of training set is 0.9921305356841013\n",
      "MAPE of training set is 3.1480360575304682\n",
      "\n",
      "RMSE of test set is 5240.439996364492\n",
      "R2 score of test set is 0.7303357985202203\n",
      "MAPE of test set is 0.09793486589778543\n",
      "---------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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KUVofm5oyBe66Cy6+GLKzS0+/aMyIGIZhpBCl8bGp33933Vht2sDjj5e2hjti3VmGYRgpxK5+bEoVLr3UGZKxY6F27QQp6jEjYhiGkWL06NGjxOMgQ4ZAbi48/DAcfngpKxYD684yDMMoJ3z5JVx7LZx6Klx9ddnc04yIYRhGOWDdOjj3XKhfH4YPh7L6zqt1ZxmGYZQDBg6E77+HCROgUaOyu6+1RAzDMNKc11+H55+HG26Arl3L9t5mRAzDMNKYn3+Gfv2gQwe4/fayv78ZEcMwjDRl82a3kFA1cduaFIWNiRiGYaQpgwfDJ584A7LPPsnRwVoihmEYaci4cXDPPdCnj5uVlSzMiBiGYaQZixbBBRdAu3aJ39akKMyIGIZhpBGbN8M558DGjfDGG+C32UoaNiZiGIaRRtxwA3z8Mbz2GrRtm2xtrCViGIaRNoweDf/5D/Tv71ojqYAZEcMwjDRg/ny45BJo3x7+/e9ka7MdMyKGYRgpzoYNcPbZbj+sN96A6tWTrdF2bEzEMAwjxfnnP2H2bBgzJnnrQQrDWiKGYRgpzKuvwlNPuS3eS/iJkYRiRsQwDCNF+e47ty/W0Ue7hYWpiBkRwzCMFCQ/H846C2rWdNN5k7EvVhhsTMQwDCPFUIUrr4S5c932Jk2bJlujwkl4S0REKovI5yIy1v/fR0Q+FZF5IjJSRKp59+r+/zzv3zIQxo3e/XsROTng3s27zRORGxL9LIZhGGXB8OEwYgTccgtkZSVbm/iURXfW1cC3gf/3Aw+ramtgJXCpd78UWOndH/ZyiMiBwLnAQUA34ElvmCoDQ4DuwIFAtpc1DMNIW2bPdosJu3SBW29NtjZFk1AjIiJNgVOB5/1/AboA//UiI4Ce/vwM/x/v39XLnwG8pqobVfUnYB5wlD/mqep8Vd0EvOZlDcMw0pLff4e//hUaNnTbu1eunGyNiibRLZFHgOuBAv9/d2CVqm7x/xcDTfx5E2ARgPdf7eW3uUddU5j7TohIPxGZKSIzly9fvqvPZBiGUeps2eK2dP/tNxg1CvbYI9kahSNhRkRETgOWqeqsRN0jLKr6rKpmqmpmo7L8gr1hGEZI/vUvmDjRrQk58shkaxOeRM7OOhroISKnADWAusCjQIaIVPGtjabAEi+/BGgGLBaRKkA94I+Ae4TgNYW5G4ZhpA0jR8KDD8L//Z/bHyudSFhLRFVvVNWmqtoSNzA+SVXPByYDZ3mx3sAYf57r/+P9J6mqevdz/eytfYA2wGfADKCNn+1Vzd8jN1HPYxiGkQi+/tp9nbBzZ3jkkWRrU3ySsU5kEPCaiNwFfA4M9e5DgZdEZB6wAmcUUNU5IvI6MBfYAvRX1a0AIjIAGA9UBoap6pwyfRLDMIxdYOVKN5Bet67bWLFatWRrVHzEVfYrDpmZmTpz5sxkq2EYRgWnoABOPx0mTIDJk93WJqmKiMxS1cxYfrZi3TAMIwkMHgzvvgtPPpnaBqQobO8swzCMMmbMGLjzTjeIfsUVydZm1yjSiIjI1SJSVxxDRWS2iKT4QnzDMIzU5Pvv4cILITPTtUJEkq3RrhGmJdJHVdcAWUB94ELgvoRqZRiGUQ5ZswZ69nRfJnzzTahRI9ka7TphxkQidvIU4CU/WyrNbadhGEbZUlAAF18MP/zgBtObN0+2RqVDmJbILBHJwxmR8SJSh+3bmBiGYRghuP12GD3aLSo84YRka1N6hGmJXAocBsxX1XwR2R1IszWVhmEYyWPkSLjjDjeQPnBgsrUpXcK0RBS31fpV/v9uuG1MDMMwjCKYMcN1Yx1zjNsXq7wNBoQxIk8CnYBs/38t7jsehmEYRhyWLIEzzoDGjd1AevXqydao9AnTndVBVY8Qkc8BVHVl5GuEhmEYRmzy891MrLVr4aOP0mdr9+ISxohs9l8RVAARaYQNrBuGYRSKqttUcdYst7CwXbtka5Q4wnRnPQaMBvYQkbuBacA9CdXKMAwjjbnzTjeYft99bn+s8kyRLRFVfUVEZgFdcWtGeqrqt0VcZhiGUSF54w247Ta46CK47rpka5N4wmx70gr4SVWHAN8AJ4lIRsI1MwzDSDNmzYLevd23QZ59tvzNxIpFmO6sN4GtItIaeAb3NcFXE6qVYRhGmvHLL24mVqNGblFheZyJFYswA+sFqrpFRP4GPKGqj0dmahmGYRiwfr0zIKtWle+ZWLEI0xLZLCLZwEXAWO9WNXEqGYZhpA+qcOmlMHMmvPIKHHJI4bK5ubkMGDCA3Nzy8yXvMEbkEtxiw7tV9Sf/nfOXEquWYRhGejB4MOTkwD33uNZIYeTm5pKdnc2QIUPIzs4uN4akSCOiqnNV9SpVzfH/f1LV+xOvmmEYRmozbJjbE6tPHxg0KL5sXl4e+fn5AOTn55OXl1cGGiaeMLOz2ojIf0VkrojMjxxloZxhGEaqkpcHl18OWVnw9NNFz8TKysqiVq1aANSqVYusrPLxbb8wA+vDgduAh4ETcN1b9lldwzAqLF9+CWedBQce6NaFVA0xStyjRw9ycnLIy8sjKyuLHj16JF7RMkBUNb6AyCxVbS8iX6tqu6BbmWhYymRmZurMmTOTrYZhGGnK4sXQsaM7/+QTaNrUjXeUN+MQxJf5mbH8wrRENopIJeAHERkALAFql6aChmEY6cCaNXDqqe532rTtBiQ7O5v8/HyGDx9OTk5OuTQkhRGmW+pqoBbueyLtgQuA3olUyjAMI9XYvNl1Yc2d67Z1j0zlLa8D5mEJMztrhqr+qaqLVfUSVT1TVT8pC+UMwzBSAVU3iD5hgtvO5KSTtvuV1wHzsISZnTUhuFeWiNQXkfGJVcswDCN1uOsuGD4cbr3VfeI2SGTAvH///hWuKwvCDax/rqqHF+WWLtjAumEYxeHFF92mihddBC+8UDE2VYwm3sB6mDGRAhFpHgisBf4DVUXctIaIfCYiX4rIHBG53bvvIyKfisg8ERkZ+UqiiFT3/+d5/5aBsG707t+LyMkB927ebZ6I3BDiWQzDMEIzaZLb0qRLF3juuYppQIoijBG5CZgmIi+JyMvAB8CNIa7bCHRR1UOBw4BuItIRuB94WFVbAyuBS738pcBK7/6wl0NEDgTOBQ4CugFPikhl/7XFIUB34EAg28sahmHsMt98A3/7G7Rt6wbSq9lHwWMSZmB9HHAEMBJ4DWivqkWOiajjT/+3qj8U6AL817uPAHr68zP8f7x/VxER7/6aqm5U1Z+AecBR/pinqvNVdZPXLc7ONYZhGOF5882PgWX84x8TyLAvKBVKqJXnqvq7qo71x+9hA/cthi+AZcAE4Edglapu8SKLgSb+vAmwyN9vC7Aa2D3oHnVNYe6x9OgnIjNFZOby5cvDqm8YRgUlNzeXBx44kdWr9+aqq3qWm80SE0FCty9R1a2qehjQFNdy2D+R94ujx7OqmqmqmY0aNUqGCoZhpBHb135srZBrP4pDmeyBpaqrgMm4LeUzRCSyUr4pbgU8/rcZgPevB/wRdI+6pjB3wzCMXaKir/0oDoUaERFpEO8oKmARaRRZXyIiNYGTgG9xxuQsL9YbGOPPc9m+Ev4sYJK6+ce5wLl+9tY+QBvgM2AG0MbP9qqGG3y3NqdhGLtMRV/7URzi7Z01CzcQLkBz3EwqATKAhcA+RYS9FzDCz6KqBLyuqmNFZC7wmojcBXwODPXyQ4GXRGQesAJnFFDVOSLyOjAX2AL0V9WtAH4vr/FAZWCYqs4pzsMbhmEURo8ePcx4hCDMYsPngNGq+q7/3x3oqaqXl4F+pY4tNjQMwygeu7rYsGPEgACo6ntA59JSzjAMw0hfwmwFv1REbgZe9v/PB5YmTiXDMAwjXQjTEskGGgGjgVH+PDuRShmGYSSK3NxcBgwYYGs/SokiWyKqugK4WkR2U9V1ZaCTYRhGQsjNzaXX9b3YePBGhl0wjNdefs0Gz3eRMFvBd/Yzqr71/w8VkScTrplhGEYpM2LSCDaeuRH2hPVb19siwlIgTHfWw8DJuIV/qOqXwF8SqZRhGEZpM2PJDMbtPg75U2AE1MIWEZYGYQbWUdVFsuMeyFsTo45hGEbp88WvX3DyyyfTuG5jbj7gZmZvnU1WVpZ1ZZUCYYzIIhHpDKiIVMV9c/3bxKplGIZROsxZNoeTXjqJ2tVqM6n3JFpmtKTPWX2SrVa5IUx31hVAf9wOuUtw3wbpn0ilDMMwSoP//fE/ur7YlaqVqjLxoom0zGiZbJXKHWFmZ/2OWxtiGIaRNvy44ke6jOhCgRYwufdk2uzeJtkqlUuKNCJ+08O/Ay2D8qpqnYmGYaQMubm55OXlkZWVxaF/OZQuL3Zh/Zb1TO49mQMaHZBs9cotYcZE3sJtjvg2UJBYdQzDMIpPbm4u2dnZ5OfnM/SNoWQMzGC9rGdS70kc0viQZKtXrgljRDao6mMJ18QwDKOEbPuIVG3Y0GsDf2z4gw/7fsgRex2RbNXKPWEG1h8VkdtEpJOIHBE5Eq6ZYRhGSLKysqi5e024CKgLt7e9nQ5NOyRbrQpBmJZIO+BCoAvbu7PU/zcMw0g6Hbt2pPF1jVm0fhGD2wzmxvNuTLZKFYYwRuRsYF9V3ZRoZQzDMIrLL2t/4cSXTuS3Lb/x3oXvcVKrk5KtUoUiTHfWN7ivGRqGYaQUS9Ys4fgRx7Ng1QLePf9dMyBJIExLJAP4TkRmABsjjjbF1zCMZLJw9UK6jOjCsnXLGH/BeI5ufnSyVaqQhDEityVcC8MwjGIwf+V8uozowqoNq5hw4QQbRE8icY2IiFQGBqvqCWWkj2EYRlx++OMHurzYhfzN+Uy8aCLt926fbJUqNHGNiKpuFZECEamnqqvLSinDMIwIwZXobTq1oeuLXdlcsJlJF03i0D0PTbZ6FZ4w3Vl/Al+LyARg25cNVfWqhGllGIZB1Er0t4dSvV91alSvwZTeUzhoj4OSrZ5BOCMyyh+GYRhlyraV6HvChnM3UHljZaZePpW2DdsmWzXDE2YX3xFloYhhGEY0WVlZPP/e82w8eyOySfh35r/NgKQYhRoREXldVXuJyNe4Feo7oKq2q5lhGAmlTrs6VLq4EnU31+Wh9g/R9+y+yVbJiCJeS2Sg/z2tLBQxDMMIMurbUWS/mU2b3dsw/oLxNKnbJNkqGTGIt2J9rP+9S1UXRB9FBSwizURksojMFZE5InK1d28gIhNE5Af/W9+7i4g8JiLzROSr4CaPItLby/8gIr0D7u1F5Gt/zWMS9SF4wzDSk+dmPcfZb5xN5t6ZfHDJB2ZAUph4RqSaiJwHdBaRv0UfIcLeAlyjqgcCHYH+InIgcAMwUVXbABP9f4DuQBt/9AOeAmd0cAseOwBHAbdFDI+X6Ru4rlvYBzcMI/VQVe798F76je3Hya1OZsKFE2hQs0Gy1TLiEK876wrcZ3EzgNOj/JQiZmyp6i/AL/58rYh8i/tO+xnA8V5sBDAFGOTdX1RVBT4RkQwR2cvLTlDVFQB+qnE3EZkC1FXVT7z7i0BP4L2iHtowjNSjQAu4Nu9aHv7kYc5vdz7DzxhO1cpVk62WUQSFGhFVnQZME5GZqjp0V24iIi2Bw4FPgcbewAD8CjT2502ARYHLFnu3eO6LY7jHun8/XOuG5s2bl/xBDMMoNYKLCLuf2p0+uX14+auXubrD1fzn5P9QScLsD2skmzBTfIeKSGd2/sb6i2FuICK1gTeBgaq6JjhsoaoqIjvN/CptVPVZ4FmAzMzMhN/PMIz4BBcRDntpGAcNPoiZa2Zy1wl38a9j/4UNb6YPRRoREXkJaAV8AWz1zgoUaUREpCrOgLyiqpHur99EZC9V/cV3Vy3z7kuAZoHLm3q3JWzv/oq4T/HuTWPIG4aR4mxbRFgD1p+1npmrZ/L0aU9zeeblyVbNKCZh2ouZwNGqeqWq/t0fRW554mdKDQW+VdX/BLxygcgMq97AmID7RX6WVkdgte/2Gg9kiUh9P6CeBYz3fmtEpKO/10WBsAzDSGGysrKosUcNuATYG67f53ozIGlKmG1PvgH2xA+SF4OjcZ/V/VpEvvBu/wLuA14XkUuBBUAv7/cucAowD8jHJS9UdYWI3AnM8HJ3RAbZgSuBF4CauAF1G1Q3jDSgdbyt82QAACAASURBVKfW1B1Yl60btnLLfrdwy/m3JFslo4SImwwVR0BkMnAY8Bnl4KNUmZmZOnPmzGSrYRgVlonzJ3Lm62dSs2pN3s5+m8y9M5OtklEEIjJLVWO+qDAtkcGlq45hGBWVYZ8P4/Kxl7N/w/0Zmz2WFhktkq2SsYsUOSaiqlOB74A6/vjWuxmGYYSiQAv418R/cWnupXTZpwvTLplmBqScUKQREZFeuK6ss3HjF5+KyFmJVswwjPLBhi0bOO/N87h32r30PaIvY7PHUq9GvWSrZZQSYbqzbgKOVNVlACLSCHgf+G8iFTMMI/1Zvm45PUf25KNFH/HAiQ9wbedrbQ1IOSOMEakUMSCePwg3NdgwjApIZCX6gX85kH//+m+Wrl3KG2e/wVkHWgdGeSSMERknIuOBHP//HGwqrWEYMdi2Er1RPtSGenXqMbn3ZDo27Zhs1YwEEWbbk+v8rr3HeKdnVXV0YtUyDCMdycvLI791vttOdQX0yO9hBqScE+/Lhq1xmyVO91uWjPLux4hIK1X9sayUNAwj9dlSsIUlBy2BRsBPUDO3Jme9YF1Y5Z14YxuPAGtiuK/2foZhGACsWL+CU145hbeWvUX3ht25ovYVvPbCa/TokZZrko1iEK87q7Gqfh3tqKpf+63dDcMw+Oq3r+j5Wk+WrF3C86c/z6VHXJpslYwyJJ4RyYjjV7O0FTEMI/14Y84bXDzmYjJqZDD14qk2/lEBidedNVNE+kY7ishlwKzEqWQYRqqztWArN75/I73+24vD9jyMmX1nmgGpoMRriQwERovI+Ww3GplANeCviVbMMIzUZOX6lZw36jzGzRvH5e0v57Huj1GtcrVkq2UkiXifx/0N6CwiJwAHe+d3VHVSmWhmGEbKMWfZHM547QwWrl7IM6c9Q7/2/ZKtkpFkwqwTmQxMLgNdDMNIYUZ9O4reb/WmdrXaTLl4Cp2bdU62SkYKYNuXGIYRl81bN3Nd3nWc+fqZHNToIGb1m2UGxNiGGRHDMAplwaoFHDv8WB76+CG6N+zOYV8cxszJ9lE3YztmRAzDiMmY78Zw2DOH8e3v33J9y+uZev1UnhnyDNnZ2eTm5iZbPSNFMCNiGMYObNq6iYHjBtJzZE9a1W/F7H6zWTdjHfn5+QDk5+eTl5eXZC2NVMGMiGEY25i/cj5HDzuaRz99lKuOuorpfabTqkErsrKyqFWrFgC1atUiKysryZoaqUKYreANw6gAvDn3Tfrk9qGSVGJUr1H89YDty8F69OhBTk4OeXl5ZGVl2Z5YxjZEVZOtQ5mSmZmpM2fawKBhRNiwZQPX5l3LkBlDOKrJUYw8ayQtM1omWy0jhRCRWaqaGcvPWiKGUYH5/vfvyX4zm89//ZxrOl3DPV3vsdXnRrEwI2IYFZACLWDIZ0MY9P4galatSe65uZze9vRkq2WkIWZEDKOCsWj1Ivrk9uH9+e/Tvm572v3UDv1eoW2yNTPSEZudZRgVBFXl5a9ept1T7fh40cf0b9afuTfP5YXHX7C1H0aJMSNiGBWA3/N/p9d/e3Hh6As5eI+D+fKKL2E2rM9fD9jaD6PkJMyIiMgwEVkmIt8E3BqIyAQR+cH/1vfuIiKPicg8EflKRI4IXNPby/8gIr0D7u1F5Gt/zWMiIol6FsNIZ9753zsc/OTBjPluDPd1vY+pF0+1tR9GqZHIlsgLQLcotxuAiaraBpjo/wN0B9r4ox/wFDijA9wGdACOAm6LGB4v0zdwXfS9DKNCs3bjWvq93Y/Tck6jce3GzOw3k0HHDKJypcrA9rUf/fv3Jycnx9Z+GCUiYQPrqvpBjG+xnwEc789HAFOAQd79RXWLVj4RkQwR2cvLTlDVFQAiMgHoJiJTgLqq+ol3fxHoCbyXqOcxjHRiys9T6DOmDwtWL+CGo29g8PGDqV6l+k5yPXr0MONh7BJlPTursar+4s9/BRr78ybAooDcYu8Wz31xDPeYiEg/XAuH5s2b74L6hpHarFi/guvyrmPYF8NoVb8VH1z8AUc3PzrZahnlmKRN8VVVFZEyWS6vqs8Cz4JbsV4W9zSMskRVyfkmh4HjBrJi/QpuOPoGbjnuFmpVrZVs1YxyTlnPzvrNd1Phf5d59yVAs4BcU+8Wz71pDHfDqHD8tPInur/SnfNHnc++9fdl9uWz6ZTfiev/cb1N2zUSTlkbkVwgMsOqNzAm4H6Rn6XVEVjtu73GA1kiUt8PqGcB473fGhHp6GdlXRQIyzAqBJu3bubB6Q9y0JMH8dGij3i8++NM7zOdnz/9mezsbIYMGWLrP4yEk7DuLBHJwQ2MNxSRxbhZVvcBr4vIpcACoJcXfxc4BZgH5AOXAKjqChG5E5jh5e6IDLIDV+JmgNXEDajboLpRYZixZAZ93+7Ll799yRltz+CJU56gaV3XOM/Ly9vp2x82eG4kikTOzsouxKtrDFkF+hcSzjBgWAz3mcDBu6KjYaQbazeu5ZbJt/D4Z4+zZ+09d9qyHSArK4vhw4eTn59v6z+MhGN7ZxlGGlCgBbz05UvcOPFGfv3zV6488kru7nI39WrU20nWvv1hlCX2PRHDSHE+WvQRA8cNZMbSGRzV5Cge6/YYHZp2SLZaRgXCvidiGGnIotWLGPT+IHK+yWHvOnvz0l9f4rx251FJbMs7I3UwI2IYKUb+5nwenP4g90+/H0W5+dibGXTMIGpXq01ubq51UxkphRkRw0gRVJXXvnmNQe8PYtGaRfQ6qBcPnPgALTJaAJCbm0t2djb5+fkMHz7c9rsyUgJrFxtGCvDZks84ZvgxnDfqPBrt1ogPLv6AkWeN3GZAIPbUXcNINmZEDCOJfPXbV/R8rScdnu/AvBXzGNpjKJ9d9hnHtjh2J1nbut1IRaw7yzCSwPe/f8/gqYMZ+c1I6lavy/l7nU+tr2vRcFFDKh9eOeY1NnXXSEVsiq9hlCE/r/qZO6bewYgvR1CzSk2u7nA1B60+iL4X9t22ONDGOoxUI94UX+vOMowyYOnapVz5zpXs9/h+vPr1qwzsMJD5V8/n7q5389Gkj2ysw0hbrDvLMBLI8nXLuW/afTw580m2FGyh7xF9uenYm2hSd/vnb2ybEiOdMSNiGAngp5U/8Z+P/8OwL4axYcsGLjr0Im79y63sU3+fnWRtrMNIZ8yIGEYpMvuX2Tz40YO8Pud1Kktl/pLxFxrPa8xf5a8xDUgE+0ytka6YETGMXURVmTB/Ag9+9CDvz3+fOtXqcE2nazhg9QEM6D2A/Px83nr+LRswN8olNrBuGCVkS8EWXv36VQ5/5nBOfvlk5iybwwMnPsCifyzigZMeYNaUWTZgbpR7rCViGMVk1YZVXPfydYxcOJK1lddyQMMDGNZjGOe1O4/qVapvk7MBc6MiYEbEMEKgqny25DOenvU0r375Kpt0EyyGajOrcc+d99Dz8J47XWMD5kZFwIyIYcRhzcY1vPLVKzwz6xm+/O1Ldqu6G63zWzP3xbnwC2xiE+9PeJ+eZ+xsRMAGzI3yjxkRwwgQ2Wp9n2P24bta35HzTQ7rNq/jsD0P46lTn+K8ducxZfwUsh/PJh/rpjIMMyKG4Xl11Ktc8uAlbDpkE3wP1aQaFxx6AZdnXs6Rex+JiADWTWUYQWzvLKNCs27TOt7+39vkfJPD2O/GUiAF8BswCy476jKee/y5ZKtoGEnHPo9rGAE2btnI+B/Hk/NNDrnf55K/OZ+96+zNaXucxvh/j2fj/I3UqlWL0286PdmqGkbKY0bEqBBsLdjK5J8nk/N1DqO+G8WqDavYvebuXHjIhWQfnM0xzY+hcqXK5Da1z88aRnGw7qyQPPbpYzSv15yu+3SlTvU6CdDMKG1Wb1jN+/Pf5+lJTzN9+XTWV1pPnWp16Ll/T7IPzubEfU+kauWqyVbTMFIe687aRbYUbOGuD+5ief5yqlSqwjHNj6Fbq250a92NQxofsm3A1ShbIjOpIq0GVWXu8rm8+8O7vDvvXaYtnMaWgi2wAZgH1eZVY+htQzm759nJVt0wyg3WEgnJpq2b+HjRx4ybN4735r3Hl799CcBetfeiW2tnUE7c90Qa1GxQ2iobMcjNzSU7O5v8zflU278aXS7vwtzNc1m4eiEAhzQ+hFNan8L373zP6MdGQ4G7rn///jzxxBNJ1Nww0o94LREzIiVk6dql5P2Yx7h548j7MY+VG1ZSSSrRoUkHuu7Tlc7NOtOxaUfq16xfClqXD6JbDiWRW7F+BR8v+phbh97K7OWzoQlQBapoFU474DROaX0K3dt0p2ndptvCys7Otq8GGsYuUK6NiIh0Ax4FKgPPq+p98eQTMcV3a8FWPlvyGePmjWPcj+OYtXQWW3UrAAc0PIDOzTrTuVlnOjXtRNuGbakkpb/vZdgCujiypSkXtjAPytWsVZOHX3iYmvvVZNrCaUxfNJ25y+cCUJnK6FKl4OcCqi+sziv3vsKZPc/cpecwDCM28YwIqpq2B85w/AjsC1QDvgQOjHdN+/bttSSMGTNG+/fvr2PGjClSrm//vnrny3fq3R/crae+cqo2uL+BMhhlMFr/vvra/eXuev4z5+vpA0/XYW8M04KCgl2675gxY7RWrVoKaK1atUpFtrTl+vfvr8C2o3///jv4FxQU6IJVC/TUf5yqHIPSC+VatsVbvXvrafeXu+tdU+/SyT9N1nWb1oV+J4Zh7BrATC2sHC7MIx0OoBMwPvD/RuDGeNeUxIjsaoFaUFCg3y3/TofNHqaXjblMm9/XfFvhyGB0tzt3085DO2vf3L76yMeP6IQfJ+jSNUv1rbfeKpUCuiSypS0XjJuaDWrq3S/frU98+oRe/vbl2nloZ617b90d4oSr0cpnV9Yrhl6hX/36lW4t2FroMxmGkVjiGZF0n53VBFgU+L8Y6BAtJCL9gH4AzZs3L/ZN8vLydvouRKxukcLkRIS2DdvStmFbLjn8EgbkDWDI0CGwJ9AI9umyD1UqVWHUt6N4bvb2FdLVC6qz8ZyN8Dvkr87n0amPUuvgWjSt25RmdZuxW7XdgOJtOR5Wdlfk8jfns2j1IhauXrj90IW0uqMV81fPZ13lddw07yaYBxk1Mmi3RzsuaHcBB+9xMO0at2PhzIV8NOkjsi6w7ifDSHXSekxERM4CuqnqZf7/hUAHVR1Q2DUlGRMpSX9+SeRUld/W/cbc5XOZs2wO78x4hwlfTKCgfgHU3lmvjBoZ2wzK1pVbWblwJYfsdwidjuhE3ep1tx11qtfZfl6tDu+MfSfUGMGYMWN4b8J7dDqhEx2O68DqDatZtWEVqzf6X///8+8+57sl31EpoxKrZTW/5/++QziVpBJ719mb5vWa06p+K9rt0Y52jdvRbo927F1nb5sibRgpTrkdWBeRTsBgVT3Z/78RQFXvLeyakg6sJ2MwOih3/InHc8RxR7B4zWIWrV7kfte438j5snXLQj1LzSo1txXcqoqi236j3SITBAqjslSmXo167Fl7T1rUa0Hzes13OprUaWKL+gwjjSnPRqQK8D+gK7AEmAGcp6pzCrumPG/AuKVgC39u+pM1G9dsO9ZuXLvj/01rWbtxLYoiCCKC4AxK5Dz4W7tabTJqZFCvej33W6PeDue7Vd3NWhKGUc4ptyvWVXWLiAwAxuNmag2LZ0DKO1UqVSGjRgYZNTKSrYphGBWEtDYiAKr6LvBusvUwDMOoiJT+qjfDMAyjwmBGxDAMwygxZkQMwzCMEmNGxDAMwygxZkQMwzCMEmNGxDAMwygxZkQMwzCMEpPWK9ZLgogsBxaU8PKGwO9FSqW+XDLvnepyybx3qssl896pLpfMeyfiWaJpoaqNYvoUtr2vHTG3ni90O+R0kksHHS1uUk8uHXS0uCmdZynOYd1ZhmEYRokxI2IYhmGUGDMixePZciKXzHunulwy753qcsm8d6rLJfPeiXiW0FS4gXXDMAyj9LCWiGEYhlFizIgYhmEYJcaMiGEYhlFizIikEBLyO7MiEuq9hQ0vjGxxwvLyYXVM+TSYrPeSrLgpzn1T/f0l4N0VJ24qRJ5K6QSQiojIySLSMsptp8QgIn8XkeNChHe7iNwMoHFmOYhIMxE5wcsVxJGrHNEvXnhetqqItA4jG/GPl/BFpIqItAqhY00ROTgoV0gcthKRhvH08nKl+k68bDLfyx5FhZcIRKRxmPuKSCURaVGUrIjsHqZAE5EOkWcuQu4CEYn5ne8ouZtE5HKvX7x3lxEJL1469O4Ng3JxwiwXeapYJGIFY3k9gGbAx8DuMfwkcN4CmAscGPQDKkdd0wRYDHwEXOzdKsUIuwUwHfgMWAg0KkS/5sBo4FUv+w+gabR+/n9L4D3gHeBzoC9ua4PoMBsAZwFNioibpsCbPsw5QOc4Or4DTAC+C8ZlVBzuCawFbgSOBeoX8hyl+k6S+V78s7wBvOjfydkBv8qB83rAUUDdIt5JWLkm/p45wNvAwbHiOvCeX/fHO8Buhei4N26LjT7+mp3iORA3U4GMGH7B8FoAXwD7h3iWX306/EsR724SMA2YBdSJk65fAp4EvgTOC/hVipJtSTnIU8U9SnxhRTyAV4C/+/NWQE9gBHBklNxDwO3+/BDgTmAccDmwR0DuZeA6/0LfBQ4v5L4vAP/05/cCV+IKpTNiyF3nz7OBVb5wyIwR5kvAzf78VF8ovBbJeAG58bjC9GbgFKB2wK9yJBHiCsg7cK3b/wOeiU7IXu4l4Bb//2GfmR6I1tGHMwX4L/A00A84CLgUqJaod5LM94IrxO8GdgN6ATP8/fePkpuAM5yXAe2i4iP4TsLKvQrcD7QFBgGDYzxr5B2+BNwF7AE8ARwHDATaRMk3Br4HPvBp6zSgDtCdQOHr4zoSh82BvwD3APtFhTckkG4OAK4CxsaI65eA23w6mQTsG+fdDfLnDwJnercOMcK71Z9fAWzCpcn9YoRZLvJUcQ/rzgqJiLTFJbSN3ukBXC1vFZArIv8IiH8C7O7PHwIW4RLUCcD1PrxMXC3lQVX9EFdDfUlETvL+lf1vA1yG/caHdzYug34C3CQid3u5+rgN1qYDqGoOLlNsAF4WkS6BZ6kJbAZ+87LvqGov4ENghIj08XItgOrAY8BWoBvwfyJyjA+qnohk4BLiPqp6q7qm9JvAESLSzcs19t0aB+Ey9Z3e/a+4QiMfeFdErono6MN5BldLHOWvfQWX8Osm4p0U873UL833IiJ1gVrAh6q6TlVfV9UjfXjjReQUL9caZ2Re8M96OdAz0oXi30klnEENI3cYzgAMUtXvcTXaM0TkKH+/3UWkkqqqiBwOtFbVm1V1Ga6gvARX+/9cRHoH3t9vOGPwNC49XIkrOAfp9u6Wg30Y8/xlD+KM7B7ApyJyQeD9fQPU8OdP+t9pwI0icqcPrxMuHd6uqkNxLZdnROSgqHfXGGewxvpwegKdcflhtIhE8uge/tle8M/0NM6Y5QM5ke4jL1su8lSJKKn1qWgHrmvgbFzt6ztcZo/4HeXdK/n/GbjawT+BVwNydYAxuGZqR+CIqHtcBTzKzs3kS3C1khxgdsC9Ca77I9IsvRJXozwB140w3btfAFyhO9ZgOgPDgQ7s2CXRCfgProZTA2jr3asBPXA17v8A5wE/42pnbYBzgCqBOLic7TW4KV6HlsAh3q0d8HDgvpk+DisHdNwdV1NtCbTGZdA3ccaiOa5boBfwVIh3Uh+XYQp9J/7/0UD7kO+lDzAyxHvpjysg474XXAEwBGgcdZ+z2V7DbYSvLeOMxP/h0trd/l1+DVxcDLn2uG6XSoG4ug24yp+Pwdf2gcOBTv68IzA0oOOpwF3+PBLOAbiWWR1//jvOmA7276MNrsX3AK5La3IgvB7AHYH/zXEtzHOB4QH3PXF5ox6utXNswK+aj/f7YuTnm4DngGHAlwH3g4GhQHX//y7gdlxX49+Aqd79X8A5UXmqk782Xp6qRrg81QqXtoPvJVaeag60KypPBdwyiJOnSlQ2lnVhnM4HrpDcB1eodA64nwVMispAp+MKty98RtkLOAmYFSPcSCJsgqsdfeITR8R9T1xBkunDbO/ds4BPA+G0wBVCLwKPAD28e1/g9Rj3/SeuRtLXZ57dgDMIFIgxrmnmn20S8FkcucN9Bj0dGBfDvxaBfmhci2JSDLkuuJrSUFzTvjbQP0pmb+Dqwt5JwO0kXE2syHfi5SNdCzu8l4B/Xf98RxXxXhoC//aZt9D3AtQEHscVqGdG4gdXcE6LE9dt/fPPAmYUVy6QziLPeyKuptwFeL+QsBqwY9fsecB7MeTOwlUwHscZjz3xxiZyT+BIHz/HBNzPjw4PZ/TG4rr5evn0WliequJ/W+NaLG8QGLPyelyBawk8wXaDfxreyPv/zXFdUhN8GowYjgHAswG5Sl6ff+EK5ULzFIGKUrw8RcAQxctTgfdXg3B56gSKyFPFOWzbkxIgItVwkys2+/+zgWtVdVKU3OG4RFkP1w+/BnhcVad6f9EYL0BEngIeUde9EO13GS4RLMUVVgNVdXKUTCNVXe7PqwD/w2WYybiEVRv4VVXH+ubxRV63lrhEfweuFVDbu7+Fa6oT0VdE8n1YGf6a1cAYVd3k/aviuoLa4Gpbjb3cGi8X6YKKzCKZAdyAK3B3A9b5+9byv61xBfgWH/ZZXm4lrrZcGSiIeieD/HPsBqxU1VH+nZyOMwDb3gmuq+Vsf7+1wOjIs0S9lydwNb46/h2M9zpFv5dr/LPUARaq6vhC3ssAXMt0N2CulzsP13JYhOuqOxQ3GNoSZ2iW4Pq1RQMzdkRkHa62vBeu1lsbGKmu64kYcnt7p91wxmyZ92+IM2QNcQZgOq7Wi3+ekeq6q4IzgD7B1e6b+Htn4FpofwAzcZWvhqq62b+/SHjV/L1XBvODiMzAFch7s70G/4r/fw2u0K6JS1f34ypQinuvOcFnFpHdcWMFt+PGuSrhupLeVtUVIjIY1yKbiBsf+Id/J5Vw3Y6jcEl/ow+vkn93V6pqHlH4PHUhLh219PF7W4zyYYf87/NUz1hhev9gnjo1Uo4UIhvJU9dFygevt+JagaN9OM1VdUth4YTBjEgRiMijuD7MG1V1ZZRfVVxNphMuoRQmtyeuUKyDK9h2kIskJhGp6jPZPrjBysLCuwz4E1iOK6ALC686rlmcpaqPiMhDwH7AfFymfFFVP/HXHIozBNVwtZSIXGVc98/HXq4yrqA9D5cIY8p52b/j+l3/jBNeTVw3zqHerzC5/VX1OxGpgetiiMhVBV4OyFXBDd529PFS2PM2xvUb11bVX6LiJvreVbyhaIkr9Au796X+PS/DDZhG5KoDIwL3roYziifhCqt9cYPQu+NauVv9/Y7EZfqtPr4jcvVwrchGqrrYh9kcZ1hb4Arsz3x4Xf2z3FdMuQd9+Bf7PBAtm6Oq93rZK3HdVQUx5B7H1eQbqOoC/+wPBuQa4Yzvy6r6gA/vQuAIXCEekdsDOB54QlWf9Xlkq38HV8XTz4d5CM5ARIc3VFUfFZEBPo38gGuJReQa4yYPBOPmWFy32T1FlA+H4cbnquG6NAvLp1VwBvE84MDCwvPXRPLUxjjh1cKN8xzmZQrT7wBV/VZEaqjqhuh7haakTZiKcOBqEb/jmrJzcDWPoH/ECLcuQq5qyPCqhZErhn7BvtA2wLf+vBJuMDmPqKmxhciNB+oFwwwhF6k9HhpPLuB+YCFyDb1blTD3DYRZWHgNIm6l+MwNihOHUXJfBP5/jOt2eR7X9dU0jtzruEHrkfiZUbiWw7eRd+rvfZSXfQ5XcEoRcs/jCuLdcTXWosLMwNX+m8eQ64CrxT+NH+cJEV4DXGWrWZzwngq8x6LCK+q+owiMxYUIb3dcuq5KjPzHjt1UkfJhJ7kSlg9VvJ4HxJOLSl/xwqteKuVkaRa65e3AtTAu9ecn4Lo8pgPdvNvd3r0oubtwtc7Skru7GHJd/fnFuC6y4PO9xfZ+/Gt8ZiktuetwNaGi5K7F1TqLkvsnru+8NMM7KmTc/DPkM19bjDjMxE2Y+D/v1hm3jqW1P54Aenm/eHKPR+QC7/zcqHvvhSt4Tw4h9zTQ3f+XELKRtCZFyGWFvHeY8J4J+SxPhbzvs5H7htAveN+yzvf34FpFYeTClEt3Aifucjm5qwGU9wPX3A7WWvvjZrZMB35i+0B6Sst5vxY+c0Zq1nfiak8tcf3WlSqiXJJ1jPi3x8988v/7Ai8E/oeVOxU3ZvI8gRYSrovy1eLKJSLM8iKXDvk+rNwulZG7GkBFOfBNzsD/TcCF6SAXnVDYXiAdj+vS+hA3uF6h5JIcNzFXCbM987+NG5wNJRfll4GrNc/D1aqPwxmuS0oil4gwy4tcKuf7ksiV5CiVAraiHbiuiLfSXc7LfgV8ZHLJuzdRhgI3+SLW1Mwi5fBjR/58P7avMB9UErlEhFle5OK855TO98UpH0I9b2kFVF4PttckjwIu8+d7ELVPUqrLxZDt68+7sfMWIRVKLoV0jLy/Dvg9vsLIseMWGJEJCB2Bv/rzSKsllFxxZCuaXBzZnfJfqstF54GSHkkvpFPxIEYXAm4O+enpJFeEbI+KLJeiOpY0PdRk5809J7JzQRlKLhFhlhe5ImTDvpeUkCutowrGNkSkEbBWo+ZMi0h7YKmqvp0OciFlcyuiXIrrWNz00BY3C24L8KuIPKWqv4nb/2upqo72l7YRkSLlVLWgtMMsL3Ih4ybse0mqXKmTCMuUrgdu6uRC4MwYfpG9dKqkulx5ehaLm7hyebiV7OfiNiXsuyty/rdUwywvcuUpbqLT1K4eSS+4U+XAzameiJs58xVuC+72Af99cIuqUlquPD2LxU1cuVPZcY+n44D3gT39/z1xOwuEkvPnpRpmeZErT3GTkLKzLAvqVD5we/4EFxwNxm1Z8QRuS5NxuC2WU1quPD2LxU1cuY7A1V4msuJ5NP5Dci8H8wAABQ5JREFUVrh9po4IK+fPSzXM8iJXnuImEWWnfU8EEJE2uG0bfvF7SKGqg3GZFdwmfTWAX1JZTlU/KC/PYnETV24pbp7/VBE5UP2mkzgDs6+I/A23ZcmaMHKqOlvcd0ZKLczyIlee4kZVZ5MAKvwGjCLSBGexV+N2Td2AW636uqr+4GVW4zatuzuF5f6C2yenPDyLxU3RcmuABbiN+BbjvrVRgNsqvSZuZfL9IeTOxm0SOLoUwywvcuUpbs5W1TkkADMibhfOfFW90c9uaIubf18Ft310K1w/dbNUllPVh8rLs1jclEiuGm4frVdwLZVfw8ip6jlx4qZEYZYXufIUN6p6DokiEX1k6XTgvmvwVJTbIbhN2e70/yXV5crTs1jclFjuBv+/eli5EHFT7DDLi1x5ipugf2kfSS/Ek33gtp5+B7cz6FEB97q4LZRbpINcOuhocZNQuXq4L+M1LY5cIsIsL3LpoGNxniVRR4XvzgIQkb1wm93th2sejsR9AOh+Vd0/XeTSQUeLm9STSwcdLW5K51kSQqKtVLocuLnWJ+A+ofkDrjm40177qS6XDjpa3KSeXDroaHFTOs9S2oe1RGIg7lvElXX7VLm0lEsHHS1uUk8uHXS0uNl1udLCjIhhGIZRYmyxoWEYhlFizIgYhmEYJcaMiGEYhlFizIgYhmEYJcaMiGEUgYg0E5HJIjJXROaIyNUBvwYiMkFEfvC/9b37+SLylYh8LSIfid9Q0ft1E5HvRWSeiNxQyD1fEJGfRORLEfmfiLwoIk1D6DpQRGqVxnMbRhjMiBhG0WwBrlHVA3FbbvcXkQO93w3ARFVtg/sOSMQo/AQcp6rtgDtx8/YRkcrAEKA77vvo2YGworlOVQ/F7Yf0OTBJRKoVoetA3JoBwygTzIgYRhGo6i/qt9FW1bXAt7jvfgCcgdsxFf/b08t9pKorvfsnQKQVcRQwT1Xnq+om4DUfRrz7q6o+jFuN3B1ARJ4SkZm+ZXS7d7sK2BuYLCKTvVuWiHwsIrNF5A0Rqb1rsWEYO2JGxDCKgYi0BA4HPvVOjVX1F3/+K9A4xmWXAu/58ya4rd4jLGa7QSqK2UBkG4ubVDUTt9necSJyiKo+htvZ9QRVPUFEGgI341YuHwHMBP4Z8l6GEYoqyVbAMNIFX4t/Exioqmui/VVVRUSjrjkBZ0SOKQ0VAue9RKQfLg/vhesa+//27t+VojiM4/j7M5jEYtAtKQOjMihlEwN/AYP4A4xms1JGgygLyqCYSDKJYsBCzBKSJIvUY/h+6Ubc68Tk86pb535/nHvu9Nx7ntPznHxY35XHdyVBKg++9wvXYfbOQcSsCpJqSAFkMSJWy6auJZUi4ioXwrsp29MOzAH9EXGXhy9JPUHeNOWxanQA25JagHGgMyLuJS2QOh5+umxgKyKGqjy/2Y/5dpZZBUo/4+eB04iY/jC9Dozk4xFgLe9pBlaB4Yg4L1t/ALRKaslJ8sF8jm8/P+c7SqSWp/XAE/AgqZGcJ8kegbp8vA90K7V3RVKtpLbqv7lZZQ4iZpV1k0pt90g6yq+BPDcJ9Em6AHrze4AJoAGYyesPASLiBRgDNkkJ+pX4um3plKRj4BzoJOU6niPimPS01hmwBOyW7ZkFNiTtRMQtMAosSzoh3cr6+9Lg9q+4AKOZmRXmfyJmZlaYg4iZmRXmIGJmZoU5iJiZWWEOImZmVpiDiJmZFeYgYmZmhb0CLdFhGOP7S7AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "🍎Forescast the next 4 days\n",
      "Degree 2:\n",
      "RMSE of training set is 1972.6904445058933\n",
      "R2 score of training set is 0.9852482948040427\n",
      "MAPE of training set is 4.316644713953852\n",
      "\n",
      "---------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# See Hubei Province \n",
    "Hubei= get_province_df(China_df, \"Hubei Province\")\n",
    " \n",
    "X_train, X_test, y_train, y_test = data_processing(Hubei, 5)    \n",
    "\n",
    "# select the best degree \n",
    "create_polynomial_regression_model(1, \"Hubei Probince\", Hubei, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(3, \"Hubei Probince\", Hubei, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(2, \"Hubei Probince\", Hubei, X_train, X_test, y_train, y_test, draw_plot = True)\n",
    "\n",
    "print(\"\\n🍎Forescast the next 4 days\")\n",
    "forecast_next_4_days(2, \"Hubei Probince\", Hubei)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Case3: Ex-hubei Province"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train dataset: data before 2020-02-09 00:00:00 \n",
      "Test dataset: the last 5 days\n",
      "Degree 1:\n",
      "RMSE of training set is 1127.8715659015575\n",
      "R2 score of training set is 0.8958137912806436\n",
      "MAPE of training set is inf\n",
      "\n",
      "RMSE of test set is 1078.7762041320639\n",
      "R2 score of test set is -2.9269788128015364\n",
      "MAPE of test set is 0.0928299151171046\n",
      "---------------------------------------\n",
      "\n",
      "Degree 3:\n",
      "RMSE of training set is 206.08833121510017\n",
      "R2 score of training set is 0.9965214540574061\n",
      "MAPE of training set is inf\n",
      "\n",
      "RMSE of test set is 1654.561940081173\n",
      "R2 score of test set is -8.237658474763073\n",
      "MAPE of test set is 0.13112523560614078\n",
      "---------------------------------------\n",
      "\n",
      "Degree 2:\n",
      "RMSE of training set is 308.10338490242503\n",
      "R2 score of training set is 0.9922252957454877\n",
      "MAPE of training set is inf\n",
      "\n",
      "RMSE of test set is 3728.657637574009\n",
      "R2 score of test set is -45.91382668572359\n",
      "MAPE of test set is 0.2931774403382968\n",
      "---------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Degree 4:\n",
      "RMSE of training set is 59.87618401053891\n",
      "R2 score of training set is 0.9997063708504659\n",
      "MAPE of training set is inf\n",
      "\n",
      "RMSE of test set is 2405.1990102350605\n",
      "R2 score of test set is -18.52081181537504\n",
      "MAPE of test set is 0.1613597707294392\n",
      "---------------------------------------\n",
      "\n",
      "Degree 5:\n",
      "RMSE of training set is 42.21159468940155\n",
      "R2 score of training set is 0.9998540666818415\n",
      "MAPE of training set is inf\n",
      "\n",
      "RMSE of test set is 371.8432964423362\n",
      "R2 score of test set is 0.5334311342878952\n",
      "MAPE of test set is 0.023329052134583337\n",
      "---------------------------------------\n",
      "\n",
      "\n",
      "🍎Forescast the next 4 days\n",
      "Degree 2:\n",
      "RMSE of training set is 740.8926311882514\n",
      "R2 score of training set is 0.9729506777963535\n",
      "MAPE of training set is inf\n",
      "\n",
      "---------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "NotHubei = get_China_exclude_province(China_df, \"Hubei Province\")\n",
    "\n",
    "\n",
    "X_train, X_test, y_train, y_test = data_processing(NotHubei, 5)    \n",
    "\n",
    "# select the best degree \n",
    "create_polynomial_regression_model(1, \"Ex-Hubei\", NotHubei, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(3, \"Ex-Hubei\", NotHubei, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(2, \"Ex-Hubei\", NotHubei, X_train, X_test, y_train, y_test, draw_plot = True)\n",
    "create_polynomial_regression_model(4, \"Ex-Hubei\", NotHubei, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "create_polynomial_regression_model(5, \"Ex-Hubei\", NotHubei, X_train, X_test, y_train, y_test, draw_plot = False)\n",
    "\n",
    "print(\"\\n🍎Forescast the next 4 days\")\n",
    "forecast_next_4_days(2, \"Ex-Hubei\", NotHubei)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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